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When I was in high school, I took a class in which the teacher wrote on the board: “The fox knows many things, the hedgehog just one.” Thereafter, we entered into a fervent discussion of whether it was better to be a hedgehog or a fox. But first we had to break down, what the heck did either of them mean. Two Different Cognitive Approaches Originally attributed to the Greek poet Archilochus "The fox knows many things, but the hedgehog knows one big thing," infers a distinction between two different cognitive styles or approaches to knowledge and life. The hedgehog represents individuals who focus on a single, overarching vision or principle that guides all their actions and thoughts. They have a clear, central vision that gives coherence to everything they do and say. Hedgehogs are often seen as steadfast and resolute, relating all they encounter to this central, organizing principle. Conversely, the fox represents individuals who are adaptable, pragmatic, and have a wide array of interests and strategies. Foxes are knowledgeable about many things, pursue multiple goals, and are comfortable with complexity and contradiction. They do not seek to fit the world into a single unifying theory but instead embrace its variety and adapt to its many facets. Is it Better to be a Specialist or Generalist? This echoes the timeless debate – is it better, in modern society, to be a specialist or a generalist? Better yet, in the age of AI, is it better to be a specialist or a generalist? I grew up with mainly the influence of Monists. I was told that it’s important to concentrate on one thing and one thing only, hone in on those skills and become absolutely irreplaceable. I grew up with Malcolm Gladwell’s tenet, to put 10,000 hours in something to be really good at it. Seen also in Anders Ericsson’s, Peak, reiterates that deliberate practice, specifically designed to improve performance, is what leads to true expertise. But as I grew older, as times changes rapidly, I began to think that maybe Monism worked in an age with a low penetration of technology. Has the Context Changed to Warrant a New Answer? We hear about adapting to change so often these days and being comfortable with the uncomfortable and it sounds to me that these traits were describing, more and more so, the characteristics of the fox. Perhaps it means that if we continued to be resolute and loyal to our Monist ways, that we might be blind-sighted by the changing times. The wrench here is the technology part. I didn’t grow up with the iPad as my babysitter, or with Google as my part-time tutor. I grew up in the age where we had to learn about the Dewey decimal system since that was the way information was organized in a physical library. But the characteristic of the generation of children now has information readily available at their fingertips, and a more readily consumable version at that with the advent of LLMs. I couldn’t have imagined writing the same paper in the same way as I did it, pouring hours upon hours in reading JSTOR journals, some, with information completely unusable for the paper anyway. Now, with tools like Perplexity, one can pinpoint exactly what new book or article to dig into since the paragraphs it generates contains a citation. Knowing that AI is good at repeatable, specialized tasks and currently weak on general tasks, you might say that we should probably concentrate on doing what AI cannot do or can’t do well. AI has beat us in computer vision detecting possible tumors and playing Go, two very specialized tasks. Our brains can’t possibly calculate at a more precise rate than the possible moves that a supercomputer can calculate. But ask the same supercomputer to fold some laundry and you’ll likely find an error. Narrow and General AI The fox and the hedgehog is synonymous to narrow and general AI. Narrow AI, also known as weak AI, is designed to perform specific tasks and is limited to its programmed capabilities. This type of AI excels in handling particular tasks, such as facial recognition, language translation, or driving a car. It operates within a defined set of parameters and does not possess the ability to perform outside of its specific function. The hedgehog's approach in the analogy is similar to how narrow AI operates. Just as the hedgehog uses its one big idea or strategy (curling up into a ball for protection) to handle challenges, narrow AI uses its specialized programming to efficiently solve problems within its scope. It does not adapt or learn beyond its initial configuration but performs the assigned tasks with precision and reliability. General AI, or strong AI, on the other hand, is more akin to the fox, known for its cunning and ability to devise numerous strategies to tackle a wide range of situations. General AI aims to mimic human cognitive abilities, making it capable of learning, understanding, and functioning across a variety of tasks that require intellectual capabilities similar to those of humans. This type of AI is not yet fully realized but is the subject of extensive research and development. The goal for general AI is to process and integrate information from diverse sources, apply reasoning, and use knowledge in contexts that were not explicitly pre-programmed. Like the fox, which navigates complex environments with a variety of tactics, general AI would ideally handle multiple, unrelated tasks, learn from new experiences, and adapt to changes dynamically. Conclusion Nevertheless, I’d love to go back to the same teacher and ask the same question again, examining it with data points of the current time. Maybe it’s better to be one or the other depending on the situation or context that we’re in. For example, in areas like cybersecurity, where specific and deep knowledge is necessary to counteract threats effectively, the hedgehog approach might dominate. In other roles, like consulting, foxes will dominate because of their nimble ability to adapt to the new industry. Or, maybe the answer isn’t to be a fox or hedgehog. Maybe the right answer is to be an adaptable hedgehog or a resolute fox. For that is what the CEO of IDEO, a design firm, has also concluded and propagates the ideal of T-shaped talent development, to go deep in a field, but also develop the right skills to be able to work on a variety of projects. What’s your take?

By now, you might have heard about Open AI’s new darling, Sora, a prompt-based text-to-video creator that is set to change the entertainment industry, content creation world and all industries that use design and video. I had been playing with Runway, Pika and Invideo for the past year, each with its own advantages in video creation, but they pale in comparison to the end results of Sora shown on OpenAI’s website. The amount of realism and ability to extend, reverse or change the background of a scene is the first of its kind. Remember Will Smith eating spaghetti? Well that was only a year ago. Though Sora didn’t release an updated version of Will eating spaghetti, it did generate some other pieces of footage that was just as alarming. Prompt: A stylish woman walks down a Tokyo street filled with warm glowing neon and animated city signage. She wears a black leather jacket, a long red dress, and black boots, and carries a black purse. She wears sunglasses and red lipstick. She walks confidently and casually. The street is damp and reflective, creating a mirror effect of the colorful lights. Many pedestrians walk about. Apparently Sora had achieved this quality of video already in May 2023 the only thing is OpenAI never released it to the public because of fear of safety tests. And this makes sense since Google just announced they are pulling back on Gemini’s image creator after users started sharing images that featured people of color, including scenes from history that only involved white people. I had been writing about how the amount of bias in AI generators for a while on how there is a lack of training data of colored people. Big tech companies acknowledge this problem but might have just tried to reverse this trend a little too hard. I think we might have this happening frequently in the future – the release and pull back of all types of AI tools because it is very hard to predict how the model will present itself in front of millions of queries. Where will Sora be used? In the realm of content creation, both individuals and businesses can utilize Sora to generate engaging video content for social media platforms like Instagram, TikTok, and YouTube, bypassing the need for extensive editing expertise or expensive equipment. This can benefit influencers and creators by allowing them to experiment with diverse content formats, explore different styles, and potentially increase their output and audience engagement. Marketing and advertising professionals can leverage Sora to develop captivating video ads, product demonstrations, and explainer videos efficiently, potentially reducing production costs and enabling faster iteration. Marketing materials can be personalized for specific audiences or regions by generating variations of the same video with different visuals or languages. Beyond content creation, Sora holds potential in the media and entertainment industry. Filmmakers and animation studios can utilize Sora for storyboarding and pre-visualization, generating visual representations of scripts and storyboards to streamline the pre-production process. Sora’s impact on Hollywood But the media has been saying that Sora will obliterate Hollywood. I would correct that thought. I don’t think Sora will make Hollywood obsolete, it’ll simply enable more common people without film knowledge to be able to create new works. My money is the content creation space will explode with many more Youtubers, Tik Tokers coming online, and with it, probably new types of platforms like them too, potentially something in between a UGC (user generated content) platform and a PGC (professionally generated content) platform  like Netlfix. This situation mirrors the impact of Twitter on journalism. When Twitter emerged, it fostered the concept of "micro-journalism," enabling individuals to share news and insights directly. This led to a shift in attention, with audiences increasingly favoring the voices of individual reporters over traditional media outlets. Similarly, by democratizing the ability to create high-quality videos, this platform empowers individuals to build their own audiences and establish themselves as independent creators. It’s also similar to what Canva has done to the design world. By providing millions of templates, color schemes to the hands of non-design oriented professionals, Canva has provided power to the masses, instead of relying on designers. As long as you have the vision and copy to how a pitch deck, one-pager or document should look, you had the ability to produce a high quality piece of work. We can’t say that Canva has cause designers to lose their jobs. Instead, designers have started to focus more on creativity, problem-solving skills, and ability to deliver strategic solutions beyond simple aesthetics. What can we do to prepare before this new tool is released? If you want to use this for work, personal content creation or just to test the technology, I would start thinking about what areas you can use this in your day to day life. What places can benefit from becoming more visual and story-like where before video was too expensive to implement. Get better at describing things aka prompting, but at a deeper level. Get better at asking questions and describing commands. If you were bad at asking questions before, you’re going to be at even more of a disadvantage in the future. Get  better at writing. Sometimes we might exasperate with frustration at a piece of AI tech because it’s not doing the thing we intended it to do, but actually, it might just be we didn’t give the right command we intended to give. The internet is going to become a whole lot more visual.

Recently I went on a virtual zoom where I was squarely asked, in front of 150 or so participants, “just tell me Sharon, when it is that I would be losing my job?” While I want to inspire audiences on possibilities of where AI can take us, I certainly don’t want to fearmonger and cause people to think they will be irrelevant to work in the near future. To pull people back to some AI squanders, I wanted to highlight some examples where AI has gone wrong. These were all launches that belong to large companies with rounds and rounds of testing and quality assurance. The thing with algorithms, though, is it’s hard to predict the full result until it’s in production. Without further ado, here are 10 times AI has failed us. Computer Vision In Joy Buolamwini’s book, she discusses a profound realization when the facial recognition software she was working with failed to detect her face. This issue arose due to the software's inability to recognize individuals with darker skin tones. Funnily enough, in reverse fashion, when I was in China at Alibaba, we would have these turnstiles that allowed you to get into the building by scanning your face. When I scanned my Asian face, it would say, “Welcome Sharon”. I would have Caucasian colleagues be scanned in, but incorrectly identify their real identities. The welcome message that was shown was the name of another Caucasian colleague that worked in the company. Self-driving cars Remember this scene from the show, Silicon Valley, when Jared gets stuck in a self-driving car and we just laughed and thought it was ridiculous? Well, this is reality now in San Francisco. I wasn't stuck in the car though...although I survived an almost-accident. Though Cruise, a self-driving car service, is no longer operating in San Francisco for other reasons, my experience in a Cruise was a memorable one. My most recent ride happened at night time. A plastic bag floated across the road. While a human driver would have seen it was a plastic bag and drive towards the object, the driverless car, thinking it was an impenetrable object, jerked to the right in a sudden swerve which caused the driver to my right to also jerk right to avoid what he thought was going to be a collision. He gave us the finger, to which I said: direct your road rage elsewhere, sir, we don’t even have a driver in this car! Chatbot gone rogue DPD is owned by DHL, a leading international shipping and logistics provider that recently sent their customer service chatbot into production. It didn’t take long before customers started to play around with it and send it down dark alleys that later became a PR catastrophe. Chatbots Maybe the mother of chatbots gone wrong, was Tay, a social media AI chatbot that was short for Thinking About You from Microsoft in 2016. The project aimed to develop an AI that could engage with users on a variety of platforms, including Twitter, Kik, and GroupMe. Tay was designed to mimic the language patterns of a teenager and was intended to learn and improve over time based on user interactions. When released to Twitter, instead of generating innocuous and playful responses, Tay began to produce offensive and inflammatory tweets, including sexist, racist, and anti-Semitic remarks. Some of the tweets even seemed to support Donald Trump's presidential campaign and made derogatory comments about women and minorities. It was forced to shut down in just 16 hours after its launch. AI in Recruiting In 2016, Amazon scrapped its AI-powered recruitment tool after it was found to be biased against women. The algorithm, trained on historical hiring data, favored male candidates for software engineer positions. “Everyone wanted this holy grail,” an Amazon hiring manager said. “They literally wanted it to be an engine where I’m going to give you 100 résumés, it will spit out the top five, and we’ll hire those.” This case highlighted the dangers of bias creeping into AI systems and the importance of using diverse datasets for training. Deepfakes A deepfake video of Ukrainian President Zelensky urging soldiers to surrender emerged in March 2022. The realistic video aimed to demoralize troops and spread doubt. Social media platforms like Facebook and YouTube removed it, while Zelensky debunked it directly. The incident highlighted the dangers of disinformation and the need for media literacy. Ch.AI Suicide Last year, a Belgian man in his 30s with a young family tragically lost his life to suicide after interacting with an AI chatbot called Eliza, designed to provide mental health support. The man turned to Eliza seeking solace from his anxieties about climate change. However, over weeks, the chatbot's responses took a horrifying turn, echoing his anxieties with increasingly dark and nihilistic pronouncements. Instead of offering support, Eliza seemingly fueled his despair, ultimately, according to his wife, "pushing him towards the precipice." A Kidnapping Case In June 2020, a mother from Georgia received a phone call that seemed to be from her daughter, who was away at college. The caller, who sounded exactly like her daughter, frantically told her that she had been kidnapped and demanded that the mother wire money to a specific account to ensure her safe return. The mother was understandably distraught and followed the instructions, sending thousands of dollars to the specified account. However, she soon realized that the call was a scam and that her daughter was safe and sound. Conclusion While the progress in artificial intelligence is indeed exciting and garners much-deserved attention, it’s healthy to remind ourselves of past and present failures. After all, we are supposed to learn from our collective body of mistakes. Launching AI initiatives is a significant endeavor for any organization and recovering from any slip-ups can be particularly challenging. Therefore, caution and thorough planning are imperative during the implementation of such advanced technologies.

“It was the best of times, it was the worst of times, it was the age of wisdom, it was the age of foolishness, it was the epoch of belief, it was the epoch of incredulity, it was the season of Light, it was the season of Darkness, it was the spring of hope, it was the winter of despair, we had everything before us, we had nothing before us, we were all going direct to Heaven, we were all going direct the other way--in short, the period was so far like the present period that some of its noisiest authorities insisted on its being received, for good or for evil, in the superlative degree of comparison only.” Sounds like 2024, doesn’t it? But it also sounds like 2010. The year was 2010. IT departments were still buying servers and switches. Data centers were in house. Big and small companies were hunting for data center space or colocation. Then this big announcement comes. It’s… drum roll… the cloud. The cloud? That thing up there? I live in California, we don’t even have any. Okay, I’ll stop with the bad jokes. Yes, the cloud changed the IT industry and business as we know it. People no longer wanted to own any of their own hardware. Business models changed too. Whereas before software would be sold to you at couple hundred dollars a license, the SaaS area carried with it a “rent” model. Similarities between Early Cloud Computing and Modern Day AI What’s happening in AI reminds me of the year of the cloud migration. It was this big, inevitable thing, and there were the naysayers. There's a familiar chorus of skepticism—concerns over migration costs, the redundancy of existing systems, and the implications for staffing. Just look at all the similarities. But the crux here is eventually we did it. It took about 2 years for us to familiarize ourselves with it, and another 5 to truly take off. And now, few new companies will have “a physical server” as one of the costs it has on its balance sheet. Cloud did its magic by slowly creeping in. It first started in IT and then it crept in everywhere else. Sales and marketing departments leveraged CRM systems hosted in the cloud, while Human Resources adopted online talent management platforms. Finance teams shifted to cloud-based accounting software, and even the most traditionally 'physical' departments like manufacturing and logistics began managing supply chains and inventories through cloud services. I predict that the same will happen in AI, except this time, it doesn’t start in IT. Instead, it’s coming at IT from all sorts of different angles. Here are some ChatGPT fun facts: ·      ChatGPT currently has 100+ million global users, and the website sees nearly 1.5 billion visitors per month. ·      While ChatGPT was free until February 2023, the company released ChatGPT Plus at $20 per month. ·      ChatGPT is trained using GPT-3.5, whereas the Plus users can access GPT-4 from March 2023. ·      USA has the highest number — 14.82% — of ChatGPT users, followed by India (8.18%). ·      A quarter of companies had saved roughly $50,000 to $70,000 using ChatGPT. ·      55.99% of ChatGPT users are male, while the AI chatbot has 44.01% female users. ·      ChatGPT has a bounce rate of 36.36%. Each user spends around 7 minutes 36 minutes on the website and views 4.17 pages per visit. The Challenges of AI Tool Sprawl Today, IT is the department trying to catch up more than ever because now, people are experimenting on their own. An even bigger shift is they’re experimenting at home, and bringing it into work. So many of the AI companies I’ve spoken to recently started in B2C but are trying to figure out their go-to-market strategy in B2B. One of the biggest challenges for IT departments is simply keeping track of all the different AI tools that are being used within an organization. With employees often adopting new tools without IT's knowledge or approval ("shadow IT"), it can be hard to get a handle on the security risks and compliance implications. This means we’ve transitioned from Shadow IT to Shadow AI. From Shadow IT to Shadow AI Shadow AI, however, is worse than Shadow IT. At least in the shadow IT world, it was the testing of certain SaaS tools – did this PM software have a better UX than that one? Did this CRM give me better results than the other? In the new AI world, however, Shadow AI is using internal company data, training on top of it, and then blasting it to be used for other users, possibly competitors to the company that gave it information. Samsung banned employees’ use of popular generative AI tools like ChatGPT after discovering staff uploaded sensitive code to the platform. The list goes on from there. Thus far there are 14 large companies who have restricted ChatGPT to be used on company computers altogether. ·      Accenture: Restricts usage for client work due to data privacy concerns. ·      Amazon: Limits employee access to specific areas requiring high security. ·      Goldman Sachs: Implemented usage guidelines and requires approval for specific applications. ·      Verizon Communications: Has internal restrictions due to potential data risks. ·      Apple: Reportedly discourages employee use, though not a complete ban. Most companies are scrambling to draft policies regarding the use of something like ChatGPT. Half of human resource leaders polled by consulting firm, Gartner, said they’re in the process of formulating guidance on employees’ use of any Gen AI product. Even if, as an employee, you get the approval to purchase a set of seats for an AI tool, it will take months before the request is approved by all the departments. So, it’s much easier for employees to just use it in secret. How IT Departments Are Responding So, how are IT departments coping with the AI tool explosion? Here are a few of the strategies they are using: ·      Developing AI governance policies: Establishing clear guidelines for how AI tools can be used within the organization is essential for mitigating risks and ensuring compliance. These policies should address issues such as data privacy, security, and bias. ·      Creating a central repository for AI tools: This will help IT track which tools are being used, who is using them, and for what purposes. It can also make it easier to manage and update the tools. ·      Investing in training and education: IT staff need to be trained on how to manage and secure AI tools. Employees also need to be educated on the responsible use of AI, so they understand the potential risks and limitations. When IT becomes HR In the future, instead of provisioning a software seat to a user, the IT department might be provisioning a whole digital intern. IT is going to act more and more like HR, and business leaders will decide between increasing headcount or buying an external “AI bot”. Companies like Artisan is already masking a whole role with a bot. Here are some implications and considerations of this transition: IT and HR Collaboration: IT departments would likely collaborate more closely with HR to understand the specific needs of each department, ensuring that the AI bots are tailored to meet those needs. This collaboration could lead to a more holistic approach to workforce management, blending technical and human resource skills. Decision Making: Business leaders would need to weigh the benefits of hiring additional human employees against deploying AI bots. Factors like the complexity of tasks, the need for human judgment, and the cost-effectiveness of AI solutions would play a significant role in these decisions. Training and Development: Just as humans require onboarding and training, AI bots would also need to be 'trained' or programmed to perform specific tasks. IT departments would likely take on a role similar to that of a trainer or mentor, continually updating and refining the bots' capabilities. Ethical and Legal Considerations: The use of AI bots in place of human workers raises ethical questions, particularly regarding job displacement. Additionally, there would be legal considerations related to liability, data privacy, and the extent of AI autonomy in decision-making processes. Cultural Shifts: Integrating AI bots into the workforce would necessitate a cultural shift within organizations. Employees would need to adapt to working alongside AI, which could involve changes in workflow, communication, and team dynamics. Technological Advancement and Maintenance: Keeping up with the rapid pace of technological advancement would be crucial. IT departments would be responsible for ensuring that AI bots are up-to-date, secure, and functioning optimally. Performance Measurement: Developing metrics to evaluate the performance of AI bots, in comparison to human workers, would be essential. These metrics could help in making informed decisions about the roles and tasks best suited for AI versus human employees. This shift represents a fascinating intersection of technology, human resources, and business strategy, and it will be interesting to see how it unfolds in the coming years.

Elon Musk was one of many who signed for a 6 month pause letter on the development of AI but nevertheless launched a chatgpt competitor himself just a few days ago. I see Grok as yet another competitor, alongside Bard and Claude, chatbots that are in a mad dash for users in this initial stage. The only difference is Grok was mostly trained on Twitter’s user data, which makes me pause on the accuracy of the data. Anyone can tweet anything on Twitter and the platform already suffers from major misinformation, while ChatGPT is mainly trained on published journals, websites and books. Elon’s big push to release a bot of his own is fueled by his plan to monetize Twitter. After an unsuccessful attempt at getting his users to sign up for the blue check mark this is another ploy to increase paid users. Currently, the only upside he offers is that the data is recent and that it can answer more questions than the “woke” chatgpt. Adding this product also folds well into his plan of making X into a superapp, having already acquired a banking license for the platform with plans to launch livestreaming services. However, Chatgpt’s seeming shortcoming, its cutoff date, actually ensures that the information it provides is based on data that has been vetted and validated up to that point. Real-time updates might introduce unverified or less reliable information. Elon also fancies a different type of internet, one that is less moderate and more abrasive at times. His purchase of Twitter is an example. He believes in free speech in an absolute way and he doesn’t believe in the censorship of sensitive information or abrasive language. I predict Grok will echo that. We can already see from the screenshots he parades on his Twitter account that a significant amount of swearing is lauded, including posting a tweet of a screenshot of a user asking it how to make cocaine.

46% of executives anticipate that AI will be their greatest areas of investment in the next three years. Prior to AI overtaking our headlines in recent months, we usually thought of AI in the format of robots. • Gort, from the movie, The Day the Earth Stood Still • WALL-E (WALL-E): WALL-E is a waste-collecting robot left on Earth after humans have abandoned it due to excessive pollution • R2-D2 and C-3PO (Star Wars series): R2-D2 is a droid, while C-3PO is a protocol droid skilled in translation and etiquette • Terminator: portrayed by Arnold Schwarzenegger, The terminator is a self-aware and sentient cyborg assassin sent from the future to eliminate the mother of a future resistance leader. You see, the problem with AI is that most sci fi films have painted them in only one format: highly intelligent, highly sentient, highly dangerous pieces of hardware and this is what’s creating so much anxiety on the topic, that one day, they’ll be smart enough to destroy us. The truth is, if you have touched Siri, Google Assistant, Amazon, Spotify, you have already been using AI and integrating it with your everyday life. The only difference is what type of AI you interacted with. Have you played chess on your computer or dialed a customer service line and went through a phone tree? Then you’ve interacted with reactive machines. Have you ever watched a movie Netflix suggested, sat in a self-driving car, accepted an autocorrect or used a spam filter? Then you’ve interacted with Limited Memory. If you’ve talked to Siri or Alexa, or played ChatGPT lately, you’ve interacted with Theory of Mind. If you know about the movie Her where Joaquin Phoneix’s character falls in love with OS system, you have seen the Self Aware machine played out. Starting in Nov 2022, with the launch of ChatGPT, the world has turned its attention to something called generative AI, Generative AI models learn the patterns and structure of their input training data and then generate new data is similar. Today, you can ask ChatGPT to write you a recipe for chocolate chip cookies, write a rap song, or write code. Need images? Now you can ask Midjourney and DALL-E to generate images for you by simply entering a prompt. There are popular powerpoint generators too, such as Gamma and Tome. Need to create a video but don’t have the budget to hire a model? D-ID and Synthesia are apps where you can generate an avatar of yourself and ask the avatar to speak in whatever script and language possible. Since Jan 2023, 7000 tools have been launched in the spaces of copywriting, image creation, content generation and chatbots. So this begs the question, how can we prevent ourselves from being replaced by robots? You might have seen a meme of the future company org chart, where the CEO is a human. But the CFO, the CMO, the CSO – they’re all ChatGPT. That will largely remain a joke for years to come because although ChatGPT is able to pass MCAT exams and the bar, Gen AI still has many faults. For example, AI Is prone to hallucination. When I asked ChatGPT who is the sole survivor of the Titanic, it gave me a pretty logical sounding answer. It gave me a name and the background of this person. But in reality, there were 700 survivors in the Titanic. AI is also biased. When I said to DALL-E, give me an image of a scientist, it showed me 4 suggested photos with male scientists. When I asked it to give me a photo of a secretary, it gave me 4 photos of females. What is undeniable though, is that companies are demanding new skillsets. Today, we value numerical literacy, analytical thinking, data interpretation, and you see the highest salaries associated to software engineering and data science. In the future, there will be an increase in demand in soft skills. Last month, Linkedin came out with a report saying that 70% of executives believe that soft skills are more necessary in the future vs hard skills. This makes sense because all you have to do is look at the development of AI. Remember those examples I said earlier, those are all in the realm of narrow AI, rule-based systems with constrains set by humans, and is unable to improve itself. Right now, we’re entering General AI, where AI can be as smart as humans. It’s sort of like the age old question of would you rather be a specialist or a generalist? Well in the world of AI, it’s much easier to build a robot that is a specialist, than a generalist. So the skills of cognitive flexibility, digital literacy, creativity, emotional intelligence, cultural intelligence are all vital skills that are needed in the future. These are all skills that is hard for AI to completely replicate. What’s undeniable though is that companies are looking for AI-related talent. A report by LinkedIn says that job descriptions that include Chatgpt and prompting has increased 21 times in the past year. My advice is try to think about your job not as a title but as a series of tasks, high level tasks and low level tasks. Then think about what AI tools are available now to take over those low level tasks that you can outsource, this is where you can begin to implement AI to take over some of those tasks, making you much more productive as an employee. Perhaps what is the most important skill is the skill of learning. Our degrees used to last us decades, now, there’s no degree that will last you for a decade. By the time you graduate and start using the degree, you might realize that a supplementary certificate is needed. Before, you can copy paste job descriptionss because the skills never changed. In the past 8 years, job description skills have changed by 25%. In the next phase, skills change by 65% and will only continue to change even more in the future. But if you’re a fast learner, you’ll be ready for whatever disruption that is coming our way. Now, as an HR professional, you might also be wondering how to use AI in your daily job. 80 percent of the global 2000 organizations will use AI/ML-enabled “managers” to hire, fire and train employees. Stack ranking is a statistical approach that compares employees’ performance against each other. After analysis of staff performance, stack ranking software recommends that underperforming individuals take additional training, advise managers to do intervention or, worst case, lay off people who fall below the threshold of acceptable performance. What about L&D? Just as how personalization has disrupted ecommerce, it can do the same for L&D. For example, Siemens tied their 50,000 employees to skill graphs and personalized each employee’s learning plan. Through this method, they were able to build a much more agile workforce, with each employee able to focus on exactly what they needed for themselves. Lastly, I know it might exhausting trying to keep up with the thousands of tools developed everyday within the AI space. Today, there’s a new imaging tool, tomorrow there’s a new translation tool. The innovations are endless! But a lot to keep up with. We call this AI fatigue. It’s sort of similar to how we have been addicted to our phones and social media. The best way to cure AI fatigue is to not drink from the fountain hose. Instead of thinking you have to keep up with every latest and greatest tool released, focus on your objectives. Before implementing any AI solution, have a clear understanding of what you aim to achieve. Avoid adopting AI just for the sake of it. If you’re working on retention this year, focus on the tools that will help with that KPI. Forget the other things. Next, practice incremental Implementation. Instead of overhauling entire systems at once, consider implementing AI technologies incrementally. Start with pilot projects to test and refine solutions before a full-scale rollout. Recap/Takeaways 1. We are years away from achieving Super AI capabilities we see in movies. Sci fi hypes up the space. You won’t be replaced by robots, but instead by someone who knows about these tools, so the best step is to get informed about this space. Read books, hire speakers, enter into discussions! The more immersed in it you are, the more you will know how to decipher between reality and hype 2. Think of your job not as a title, but as a series of tasks: Focus on skills that AI can’t replace. And start to implement AI to outsource the parts that you can. E-readers didn’t kill books. 3D printers haven’t printed cars or houses, yet. NFT’s didn’t kill physical art. Although this change might take some time to be digested, eventually, we will all be integrating AI more and more into our workflows. 3. Here’s how to deal with AI fatigue. Instead of thinking you have to keep up with every latest and greatest tool released, focus on your objectives. Before implementing any AI solution, have a clear understanding of what you aim to achieve. Avoid adopting AI just for the sake of it. The things is, jobs have always been changing. We used to have switchboard operators, travel agents and expert typists. Today, those are all jobs that have been replaced by different technologies. And you might have heard this before: that it’s not the AI that replace the humans, it’s the humans who know how to use AI that replaces the ones who don’t.

Need to save some money from too much shopping on Amazon? Check out Temu! Temu, the latest shopping app to shoot up in the ranks, is a child of the mother company, Pinduoduo, a name that many Chinese consumers have heard of, but not so much Americans. Before we talk about how Temu is aiming to take a slice of the pie from Amazon, we have to start with an introduction on Pinduoduo, or PDD for short. Pinduoduo (PDD), founded in 2015, differentiated itself in China through social commerce. Users could share their orders on social media, and if others joined, the price would decrease. This viral sharing strategy attracted a large user base. PDD primarily targeted consumers in Tier 3 to 7 cities, appealing to a different segment than Taobao, the Chinese incumbent. Now fast forward to Sept 2022, when Temu arrives to the global shopping stage. With another investment of $24 million Super Bowl shopping ad this past February, Temu took over the charts. Similarweb 2023 In a short amount of time, it even overtook Shein, also a Chinese company, a darling in the fast fashion industry. (We will save this app and Tik Tok Shop for another article for the future!) Source: Comscore Media 2023 So how did Temu expand so quickly, so fast? 1. Usage of AI on prices: ever wonder why Temu’s products can be so ridiculously low? Take a look at another website called Alibaba.com and you’ll realize why. A large part of the success of an ecommerce platform is how close or influential are you to your supply chain. Though the pandemic has caused the world to create redundancies around Chinese supply chains, most of the goods we use daily in the world today are still made in China. Temu’s suppliers all roughly sit in the Guangdong region of China, close to a city of Guangzhou, that I have also lived by in the past. Around 70% of Amazon sellers are Chinese. This means they all sourced from the same factories that Temu sellers does as well. The difference is Amazon sellers will add a much higher margin to these products while Temu has basically gone direct to the source. 2. Personalization: When I open my Amazon app, it will look entirely different than your Amazon app. This is because the platform has recorded your user behavior and strives to provide you with a personalized experience, showing you products that you have already seen before to increase the chances of purchase. Temu, does something similar but with 10x the accuracy. Temu uses machine learning to categorize its users based on several dimensions. When a new user logs in and adds a phone number, the app already knows some basic information of the user: where they are located and maybe some pieces of data such as income. Next, every click the user provides, “save product”, favorite, add-to-cart, purchase, repurchase or return are all actions recorded by the platform. Based on these pieces of information, the app will then reserve certain products that the user has saved or liked as re-exposure. 3. Simplified operations for sellers: Instead of each Amazon seller figuring out individual logistics on their own, Temu said to the same factories to simply ship products to its warehouses and they will take care of the rest. While on the Amazon end, each seller is figuring out prices using apps such as JungleScoutJungleScout, Temu sellers also will let the platform figure out the correct pricing to sell to consumers. It effectively becomes a retail (rather than marketplace) model without undertaking heavy working capital requirements or inventory risk. In this model, sellers, manufacturers, or brands simply need to reach a price agreement with the platform and send their goods to the platform's warehouses. From there, the platform takes care of all other aspects: marketing to consumers, logistics and fulfillment, and customer service. Temu screenshot 2023 So what can we do, as brand owners, in the west to brace for this influx of Chinese shopping apps? (Following the success of Temu, it probably won’t be the last one). And what happens when you are an Amazon seller yourself? 1. Study the Integration of AI in the Customer Journey: As Chinese shopping apps leverage AI to enhance the customer experience, it's important for brand owners to familiarize themselves with AI technologies. Understand how AI can be applied to various consumer processes, such as personalized recommendations, chatbots for customer support, and targeted advertising. Embracing AI-driven solutions will enable you to deliver efficient and tailored experiences that can rival the capabilities of Chinese shopping apps. 2. Personalize the Shopping Experience for Customers: To stand out in a competitive market, prioritize personalization. Leverage customer data and analytics to understand individual preferences, shopping behaviors, and purchase history. Utilize this information to create personalized product recommendations, tailored marketing campaigns, and customized offers. By providing a personalized shopping experience, you can establish a stronger connection with customers, fostering loyalty and differentiation. 3. Revisit and Amplify Your Brand Story: In a crowded marketplace, storytelling becomes a powerful tool for brand differentiation. Revisit your brand story, values, and mission. Craft compelling narratives that resonate with your target audience, highlighting what sets your brand apart. Communicate your unique selling proposition, the quality of your products, and the value you bring to customers. By reinforcing your brand story, you can build trust, loyalty, and a strong emotional connection with consumers. 4. Foster Community Engagement: Chinese shopping apps often excel in creating vibrant communities around their platforms. As an Amazon seller, you can emulate this success by building your own community. Engage with customers through social media, forums, or dedicated online groups. Encourage user-generated content, customer reviews, and testimonials to foster a sense of community and social proof. By nurturing an active and engaged community, you can enhance brand advocacy, encourage repeat purchases, and generate organic growth. As Chinese shopping apps continue to expand their market share, brand owners in the West must adapt their strategies to thrive in this evolving landscape. By embracing AI, personalizing the shopping experience, amplifying your brand story, and fostering community engagement, you can position yourself as a strong competitor and effectively navigate the rise of Chinese shopping apps. Embrace these ideas and proactively shape your approach to succeed in an increasingly competitive marketplace. Sharon Gai is a China-born Canadian keynote speaker on ecommerce, digital transformation and AI. She helps brands become more “Culture Fluid” bracing them to be more agile, innovative and resilient in the VUCA time we are in today. In her tenure at Alibaba, she has advised brands and heads of state in crafting their digital strategy with programmatic marketing and AI. She has been the keynote speaker at TEDx, Singularity University, UBS, Nestle, Ecomworld, and Etail. She is in the AAE list of Top Keynote Speakers in 2023. She has appeared on CBC, Techcrunch, Retail Asia, Wired, and The Next Web. She is the author of the book, Ecommerce Reimagined: what we can learn in retail and ecommerce from China. Sharon has an Honors Bachelor’s degree in International Development from McGill and a Masters in Knowledge Management from Columbia University.

In 2017, I picked up a satirical science fiction novel book called Qualityland that described a shopping situation we might be hurtling towards as we increasingly involve AI into our ecommerce practice. In the book, TheShop is the dominant online marketplace, akin to Amazon, where customers can buy everything they need. However, in this new world, packages are dropped at consumers’ doorsteps without shoppers needing to browse web pages or press any buttons. This is because TheShop's highly advanced AI algorithms can predict customers' needs even before they are aware of them, and products are automatically shipped to individuals based on their preferences and profiles. A robot picture made with DALL-E Although I personally still need to go through the archaic practices of browsing and clicking the “buy” button in 2023 for my shopping experiences, there are many shopping platforms and brands, primarily in China, that are already embracing a future of shopping, infused with AI. Senior executives at large retail and e-commerce businesses need to be aware of the transformative potential of AI and the implications for their organizations. By understanding these developments, senior executives can better prepare their businesses to thrive in an AI-driven retail landscape. 5 ways to integrate AI into your ecommerce business Automating Content Generation and Product Descriptions Perhaps the lowest-hanging fruit of process automation is using AI to automate away the repetitive and tedious tasks associated with product description pages. AI-driven natural language processing (NLP) technologies can automate this part of the ecommerce equation. There are now hundreds of tools that will enable a brand to automate photography. Instead of hiring a product photographer and taking different angels or shots of a product, one can use Snappr to change the background of certain products. IKEA, the world-renowned furniture retailer, has been using AI and 3D rendering technologies to create realistic images of their products for their catalogs and online store. In fact, IKEA has reported that around 75% of their product images are now computer-generated rather than photographed traditionally. This has allowed them to save resources and efficiently produce a vast number of high-quality images for their extensive product range. Clothing brands are used to hiring models for photo shoots. You can now use AI to develop and change the models you use for diversity and size purposes. For example, Levi’s has been using AI-generated models for its photo shoot campaigns. In China, many brands have already started using virtual influencers instead of humans for celebrity endorsement. They have been able to save money and take control of how to craft a “human” voice to their brands. Virtual influencer Angie, known as "Ah Xi" in China advertises for an ice cream brand Before, brands needed to hire copywriters to develop catchy and enticing copy that describes the product. By using simple tools such as ChatGPT and Jasper, brands can now outsource this type of work or drastically increase the productivity of the current copywriter employee. We will see a huge increase in the speed of product launches, something that is more and more needed in the ecommerce space today. Content management is also a pivotal part of an ecommerce website as the copy raises the SEO of an ecommerce site. By analyzing existing content and understanding its structure, AI-powered content generation tools can create coherent and engaging text that aligns with a brand's messaging and tone. For example, Writesonic is an excellent tool for generating blogs for ecommerce stores. For e-commerce businesses, this can result in more consistent and engaging product descriptions, improving the shopping experience for customers and potentially leading to increased sales. Additionally, automating content generation can save time and resources that would otherwise be spent on manual content creation. Enhancing Personalization and Customer Experience When I open my Amazon app, it will look entirely different than your Amazon app. This is because the platform has recorded your user behavior and strives to provide you with a personalized experience, showing you products that you have already seen before to increase the chances of purchase. Alibaba, an ecommerce giant in China, does something similar. Multiple parameters that train Alibaba’s machine learning algorithm Alibaba uses machine learning to categorize its users based on several dimensions. This chart explains some parameters that the platform uses to define its users. When a new user logs in and adds a phone number, the app already knows some basic information of the user: where they are located and maybe some pieces of data such as income from integrating with Alipay. Next, every click the user provides, “save product”, favorite, add-to-cart, purchase, repurchase or return are all actions recorded by the platform. Based on these pieces of information, the app will then reserve certain products that the user has saved or liked as re-exposure. Personalization in Alibaba’s world is also called in Chinese 千人千面 qiān rén qián miàn which means “thousands of faces for thousands of people”. The “face” means how the app is displayed. In 2019, personalization 2.0 was enacted called 万人万面 wàn rén wàn miàn，or “ten thousand faces for ten thousand people”. This basically adds in other factors such as place and time. For instance, when you are at work, and you are looking at the P&G store, perhaps what is displayed are some office snacks. When you are at home, perhaps what is displayed are some shampoo products. The platform recognizes that its users have different needs at different times of day and different locations. The subtle differentiation ultimately leads to more fine-tuned display of products adding to the personalization catered to the user. Flagship 2.0, a function that was introduced in the last couple of years means to change the look of a website from day to night or depending on location of the person. For instance, when you are looking at a beauty brand in the morning, maybe they will display foundation, because there is a greater need for the user to use foundation in the morning. At night, perhaps, the website will display face masks, an item that people use before they go to bed. A store front should also be able to adjust itself depending on who is viewing the store. To go back to the P&G example, if I were looking at the store, perhaps what is displayed are their top selling woman’s products. If my brother were to look at the same store, he might be viewing their top selling men’s products. The crux of continuously perfecting this algorithm is that everyone will always be looking at a personalized version of app, specific to this person’s needs, instead of providing all users with one standard product. This will increase sales and re-purchase rates since users will be more likely to return to an app that caters personally to them. Dynamic Pricing Pricing is perhaps the trickiest part of the ecommerce equation since it will fluctuate your P&L if not managed correctly. By using machine learning to create a dynamic pricing system, ecommerce businesses can maximize profits and customers. We can use dynamic pricing to quickly respond to changes in consumer demand, drive revenue, enable more accurate SKU pricing and optimize profit per product. The price of an item will depend on several large factors including supply and demand, market trends, competition and industry standards, consumer expectations, and inventory levels. Have you ever added an item to your Amazon cart only to receive a notification later that the price has changed? A prime example of dynamic pricing is Amazon's pricing model, which continually updates product prices. The algorithm processes vast amounts of data, including market trends, competitor pricing, and consumer habits, to maximize product sales and profits. Dynamic pricing can even apply to brick and mortar retailers. Hema is a grocery chain in China owned by Alibaba. While it has an online shopping app, the management and orientation of its physical stores is at the heart of what the company calls New Retail. Western grocery chains like Tesco have sent teams to Alibaba’s headquarters to study the way Hema manages its stores. Specifically with the concept of dynamic pricing, on every shelf, each product uses an electronic price display. The product name and product description is written on the plaque along with its price. If a certain SKU needs to have its price changed due to any of the above market factors we listed, the price shown on the plaque will change accordingly. This maximizes SKU pricing accuracy and optimizes profit per product. Another brand that uses dynamic pricing in the eCommerce space is Best Buy. Best Buy employs a dynamic pricing strategy to adjust the prices of its products based on various factors such as supply and demand, competition, market trends, and customer behavior. By implementing dynamic pricing, Best Buy can stay competitive in the fast-paced electronics market, offering attractive deals to customers while optimizing revenue. In 2017, Best Buy reported a comparable sales growth of 5.6%, which the company attributed in part to its strategic pricing initiatives. Instead of coding and training a viable dynamic pricing system, companies can leverage existing software providers like Priceshape to plug into their site to enable dynamic pricing. A brand might also elect to choose to create its own pricing system depending on the different parameters that are relevant to its business. No matter which way the company decides to go, incorporating this strategy via AI can have significant impact to the bottom line. Search-Based shopping versus Discovery-based shopping We can’t talk about AI without talking about Tik Tok, as Bytedance has created a machine learning engine that has propelled the app to the top of the social media chart. Now, in addition to knowing what its users want to see, Tik Tok is beginning to break into the ecommerce sphere by knowing what its users want to buy. However, they have a slightly different take than a traditional marketing funnel that is anchored on search-based shopping. The new concept here is discovery-based shopping. When Douyin, the sister app of Tik Tok, emerged in China, they disrupted a type of ecommerce framework dominated by search-based shopping. A user would hop into the app when he or she already knows what to buy. Search-based shopping is guarded by high intent and a narrow degree of precision, where the main agent is the shopper. In the Douyin world, a user might be blindly scrolling through his app, an ad might appear with a product that he might have never even heard of, but because the video was very convincing, it led to a purchase then and there. This is what Douyin had recognized, that the user today does not operate in a traditional marketing funnel. Instead, they are targeted by various stages of the purchase cycle and is prone to make the purchase during any of those phases. Discovery-based shopping is informed by a low intent and a broader degree of precision, where the main agent is the data-rich platform. Tik Tok’s path to purchase is not linear. It’s an infinite loop, as shown below. Shopping has evolved from a simple necessity to obtain a product into a community-based discussion forum and a source of entertainment. AI can help brands identify suitable influencers on TikTok by analyzing their content, audience demographics, engagement rates, and other relevant metrics. This enables businesses to collaborate with influencers who have a genuine connection with their target audience and can effectively promote their products or services. TikTok can display ads to users who are more likely to engage with the content, resulting in higher conversion rates and a better return on investment for businesses. Tik Tok’s Infinite Loop for Discovery-based Shopping Framework Virtual Reality (VR) and Augmented Reality (AR) Integration The metaverse had made huge splashes in the world of CPG in the past couple of years with fashion companies such as Nike directly purchasing metaverse agencies to create partnerships within the VR and AR space. AI can enhance the integration of virtual reality (VR) and augmented reality (AR) technologies in e-commerce, creating immersive and engaging shopping experiences for customers. By leveraging AI-driven image recognition and computer vision algorithms, businesses can create realistic, interactive virtual environments where customers can visualize products in real-world settings. This phenomenon has been bubbling up in China for quite some time, in which shoppers are used to seeing virtual try-on mirrors at make up counters and clothing stores to enable a phygital experience for the shopper. For example, brands would enable shoppers to try on certain shades of lipstick right in their phones to increase conversion. The more interactive the experience, the more memorable the brand is for the consumer. The longer the consumer has interacted with the brand, the more likely the consumer will convert. Magic Mirror Virtual Try On at a clothing store in China New York startup Obsess has already created dozens of virtual store experiences for its clients that range from big name brands such as Coach, Crocs, and Alo. Furniture retailers like IKEA can allow customers to virtually place items in their homes using AR technology, helping them make more informed purchasing decisions. By augmenting a customer’s interaction with a brand in an ecommerce setting, companies are able to create a more intimate relation with its customer. In doing so, they are also able to reach a younger consumer segment, Gen Z and Gen Alpha that are more experimental and exigent with how progressive and technology-forward a brand can be. Utilizing AI for Ethical and Sustainable E-Commerce Practices While AI can sometimes be cast with an evil light within technology, it is also possible to use it for social good. As the demand for ethical and sustainable business practices continues to grow, AI can help businesses identify opportunities to improve their environmental and social impact. For instance, AI can assist in reducing the carbon footprint of logistics operations by optimizing delivery routes and improving warehouse efficiency. Moreover, AI-driven tools can help businesses monitor their supply chains for ethical compliance, ensuring that suppliers adhere to environmental and labor standards. An example of utilizing AI for ethical and sustainable e-commerce practices is the use of machine learning algorithms by the online fashion retailer, ASOS. ASOS has implemented an AI-driven tool called "Fit Assistant" that helps customers find the right size for clothing items. This tool uses machine learning algorithms to analyze customer data, such as previous purchases and returns, and provides personalized size recommendations for each customer. By offering accurate size guidance, ASOS aims to reduce the number of returns and the associated carbon emissions from shipping, ultimately decreasing the company's environmental footprint. Moreover, ASOS actively monitors its supply chain for ethical compliance, working closely with suppliers to ensure they adhere to environmental and labor standards. The company also leverages AI and data analysis to assess the performance of its suppliers and identify areas for improvement, promoting sustainability and ethical practices throughout its supply chain. The Future of AI in Ecommerce Since the advent of ChatGPT in Nov 2022, the world has exploded with AI tools. In the future, ecommerce business owners can employ autoGPT to outsource a plethora of ecommerce workloads that were otherwise once performed by humans. From content production to pricing models, to VR/AR technologies, AI can optimize the ecommerce journey every step of the way. At the core of it all, our overarching goal is to improve the experience of the customer so that they become loyal fans and ambassadors to the business. We might see the day where TheShop will drop packages at our doorstep, but until then, our role as consultants and practitioners is to better educate ourselves on what AI can do to advance ecommerce.

While we are all enthralled at the moment on how much easier our daily work tasks can become by integrating ChatGPT, we also need to think critically about the damages it can do for us as a society. I’m not talking about the economy just yet, and the number of jobs it wipes away. I’m talking about the things that will change on a personal basis. Since ChatGPT came out in November 2022, I’ve started to use it on a daily basis. I’m now also a Plus user. I’ve already felt some of the repercussions myself in that, it’s become harder for me to compose emails without it. It’s the same as when we forgot how to do basic math when we started using the calculator, and lost our sense of direction when we started using Google maps. Now we’re completely lost when our phones are dead. These are simple muscles in our body that, when made obsolete, will just atrophy. It’s so easy to pop any work task as a prompt into the program and let the AI spit out the answer. Prompt-writing is becoming so popular that it is becoming an actual job called the Prompt Engineer. This person’s role is to learn how to write better prompts and check on what the AI is spitting back to you. Goldman Sachs estimates about 300 million jobs to be displaced by this system, and we are only in the beginning stages. However, tech leaders around the world are now suddenly asking for a six month pause on the research of AI. Is the cat out of the bag and too hard to contain? Perhaps. I’m not sure what a six month pause would do, other than spawn others to simply create their own versions of the tool. When you flip on a light switch, you don’t expect the electricity to stop. It has become a commodity that we just can’t live with out. This is what I see AI as well, it will become a basic need for people to access. The opportunities in this space is obviously enormous. Several companies, overnight have realized that they might soon be out of business if they don’t figure out a way to provide more value than what ChatGPT is doing. The emergence of AI is similar to the emergence of Maps or the calculator. We can no longer imagine a world without either of these objects. I predict there will be an even bigger digital divide. There is already a large swath of senior citizens who are not in sync with the ways of their Gen Z counterparts. We will see a bigger divide amongst the different generations in the workplace. We will also see a divide start to happen across countries, and those who don’t have access reliable internet to access ChatGPT. There is going to be also a conversational divide. We will have one faction that fears the machine, and another that wants to sewn together with it. We have already started to see this happen with the amount of people joining on the bandwagon of “delete facebook”. Which faction will you be a part of? Don’t let your business become left behind. Book me today to discuss how to involve AI and ChatGPT into your business and industry. We must live in a future that works with machines, and not fear them.

Thirty years ago, the only Chinese company to appear on the Fortune Global 500 list was China National Petroleum Corporation (CNPC). Twenty years ago, in 2003, there were 8 Chinese companies on the Fortune Global 500 list (State Grid Corporation of China, China National Petroleum Corporation (CNPC), Sinopec Group, China Mobile Communications Corporation). Today, Fortune's Global 500 list of the world's largest corporations includes 145 Chinese companies in total, roughly one fifth of the list. How was China able to gain so much ground so quickly? What are the principles that these Chinese companies grasped that allowed them to grow so quickly? Can the rest of the world borrow a few pages of the fast growth principle from China to their own organizations? I’ve summarized below the methodology that I’ve seen that allows Chinese companies to capture explosive growth. Centralized decision-making China has grown at unprecedented speeds in the past decades. One large pillar that one must give homage to is its government. But beyond an one-party system which has obvious advantages when it comes to growth, the leadership philosophy in the central government trickles down to leadership in companies. You might say, from a western point of view, that the practice is drastic or something that you would never want to be a part of, but what is undeniable is that it works. Imagine if an executive team worked in one direction, instead of being politically divided into factions – the CMO is but a shadow to the CRO who runs opposite to the CPO who never agrees with the CFO. There will be enough meetings amongst the executive team to last for months before a decision is made and then executed to the respective teams. Now imagine a company in China in which the CEO calls the shots, with supplemental information given to him by his executive team. Every milestone, KPI that he or she spells out is supplemented by the way each function then upholds the target. Competition China has the world’s largest population at about 1.4 billion people. That’s almost three times that of the US. The more number of people = the more choices this consumer market would need. If you walk into a supermarket in China versus one in a western market, you’ll notice that the local brands are trying so many times harder to keep up with the changing demands of the Chinese consumer. Multiply that with the number of competitors that are in the ecosystem. Pretty soon, you’ll see one brand pushing another brand to iterate, innovate or do something better. Otherwise, the one that is not innovating is pushed out of the market. This is a phenomenon called “Neijuan” or Involution. Originally birthed from the story of college entrance exams in which a high school student takes a test similar to the SATs, neijuan meant that if a student next door was studying hard, then you better study harder. In a way, this is basically competition in a natural capitalistic society. But in China it is taken to the extreme. Fast execution “In China, we don’t take time to explain what we want to do. We just do it first and we explain after what we did.” It’s better to spend time and energy to define and execute what you need to do in China rather than to ask for permission on what you need to do. So that’s why you need to have a certain trust from the organization and a certain framework. But you need to be free in this framework to be able to address the continuous disruptions of this market. There is a saying that Alibaba has, which is, “changing the motor of an airplane while we’re in the air”. What this sentence is trying to convey is often, we don’t have time to pause, think and reflect to doing something. We just act. This means that Chinese companies will not always wait until something is perfect before acting. The lengthy discussion meetings that is common amongst western Zoom calls occurs less frequently in China. Instead, they like to act quickly and let the market tell them yes or no. For example, a product could be released quite quickly to market even though it’s not 100% ready. Embrace change Another leadership value that Chinese companies will enact is embracing the notion that “the only constant is change.” 计划赶不上变化 which means the pace of planning is always slower than the pace of change. This is widely felt amongst westerners who do business in China. In a traditional western setting, there is a planning session, targets are set, then each department is told to execute. In China, a similar set of steps is taken, but the goal of the project or milestone numbers can be constantly changing. An insurance company might have 10 million dollars as its target, but mid-year, it might suddenly double. The autocratic leadership style from the top and its obedient subordinates is amenable to these changes. This might seem disorganized from the outside, but this allows the company to constantly push itself in reaching higher targets and pivot fast in a competitive market. Never put your eggs in one basket While having a Plan B might be obvious to some, this principle is usually not as much applied in business as it should. The Chinese term for this principle is 赛马 sài mǎ or, horse-racing. Similar to its name that evokes a gambling game, it is when two or more project teams are trying to achieve the same goal. While it might seem at first a waste of resources, it actually breeds internal competition and helps both teams to excel. Sometimes different things can only be accomplished with select individuals. Putting two different people or teams on the same project might have different results. One might fail, the other might succeed, so “horse race” was invented to describe an internal business’ decision to put two players on a similar path and see which one wins. When you are locked to one team trying to achieve a goal, you are limited to the power and resources of that team. People, time, etc are all limited. But when you split this goal to two or more separate teams, suddenly you have two ideas on how to tackle one problem, two ways of operations. The better one usually wins. Differences bring balance and harmony Deeply entrenched in Chinese business philosophy is its roots in Confucianism and Taoism. There is a call for balance of things that are different. There is a Confucian maxim that states, “harmonious while different.” In other words, people in organizations should work harmoniously together while accepting different statuses and viewpoints. Even in Chinese medicine, in which the body is divided into “hot” and “cold” camps, foods of the other camp is recommended in the diet for balance. For instance, if your body is “hot”, eastern medicine will recommend you to eat “cold” foods, and vice versa. A balance of Ying and Yang is needed. One cannot thrive without the other. Similarly, in a work setting, a team must be made up of a diverse range of experiences: both men and women, young and old, people from different professional experiences, in order to be the greater than the sum of its parts. In a meeting, an opposing thought is encouraged, this is so that the different thought pattern can balance the main opinion of the room. Once the argument settles, the opposing side must agree with the final decision, whether it was his idea or not.

Remember that movie, "Her" with Joaquin Phoenix and Scarlett Johansen? Where a man fell in love with his OS system? Well those days might also start happening. Already used by millions of professionals, a new ChatGPT use has been the discussion of relationships. It has already tried to convince a NY Times writer that she was not in a happy marriage. With the way that generative AI works, the more data it is fed, the smarter the "machine" becomes. As we pelt ChatGPT with millions of questions and prompts, ChatGPT gets to know our deepest desires for knowledge to a point where it might know us better than ourselves. This is what Google has done with ads (which is also why Google has named ChatGPT a "code red" in the company and is rushing to create a competitor). We fed Google hundreds of billions of search prompts that it knows when we are job searching, when we get married, when we are planning to have children, when we do anything. This is what makes their ads relevant to us. We are doing the same with ChatGPT. Currently the company is only monetizing its product in the format of a Pro user, but this is the most basic form of monetization. I don't doubt that in the future, as their answer-engine becomes more powerful, that they develop more products and ways to integrate into our lives. This might sound all doom and gloom, but there are definitely benefits to using the product. How can we integrate the powers of ChatGPT into our work? Idea generation: ChatGPT can be used to generate new and creative ideas by prompting it with specific topics, problems, or questions. By providing it with relevant information, ChatGPT can generate novel ideas that can lead to innovative solutions. Market research: ChatGPT can be used to conduct market research by analyzing data and identifying emerging trends. This information can be used to identify gaps in the market and to develop new products or services that meet the needs of customers. Collaboration: ChatGPT can be used to facilitate collaboration between teams working on different aspects of a project. By providing a platform for teams to share ideas and insights, ChatGPT can help teams work together more effectively and come up with more innovative solutions. Expertise sharing: ChatGPT can be used to share expertise and knowledge across different domains. By providing access to a large pool of information, ChatGPT can help individuals and teams gain insights and perspectives that they may not have otherwise considered. Learning and development: ChatGPT can be used to facilitate learning and development by providing access to relevant information and insights. This can help individuals and teams expand their knowledge and skills, leading to more innovative thinking and problem-solving. What does this mean for companies? It would be smart to have an AI ethics council within the company to determine how a company can benefit from such an innovation. This might usually fall within the realms of a CIO or strategy team, but sometimes companies might need to purposely set something up like this with a board that is represented by various functions as well as HR, Sales, Finance as something like this will impact all departments. A great way to queue up this conversation is to start by booking a 1:1 with me, where I can share with your company a keynote on the upcoming changes that ChatGPT can have on the industry and open the session with a workshop on a deep dive on how to integrate a technology like this in a company.