You're a CEO who needs to pivot to Generative AI. What do you need to do right now? - Part One

As CEO, it’s likely that part of your responsibilities in 2024 will be creating a Generative AI future for your business. Businesses everywhere are rushing to complete this transformation… and falling over themselves in the process.

How can you pivot to Generative AI in a way that builds a sustainable Generative AI-based future, without threatening what you’ve already created? This series of two articles looks at four areas to focus on in order to complete a successful pivot to Generative AI.?

How many semiconductors does it take to turn a lightbulb on?

At just 500 miles long and 155 miles wide at its widest point, the Malacca Strait may be the smallest strategically important stretch of water on the planet.

China has long worried that the strait between Sumatra and Malaysia, with Singapore at its Southern tip, could easily be blocked by its rivals, freezing the country's oil supplies from the west.

But, as Chris Miller tells in his bestselling book Chip War: The Fight for the World's Most Critical Technology , China is nowadays more concerned with a bigger problem.

China has pivoted its focus towards the supply of silicon chips, used in everything from cars to washing machines.

During 2020, the silicon chip industry was hit by a perfect storm of issues. Global and localised Covid lockdowns, a major fire at a production facility, geopolitical tension and, eventually, war. Chip production fell and the knock on impact was huge.

In the US, car manufacturers need somewhere between 1,000 and 3,000 chips for every single car they build. If even one is missing, the car cannot roll off the production line. In just one year of the shortage the US auto industry made 7.2 million fewer cars, losing an estimated $210 billion in revenue in 2021 alone.

China, the US and other major economic powers now have a new problem to fixate on, along with traditional concerns like security, economic growth and health care.

How do you pivot, at speed, from being concerned mainly about oil and the Malacca Strait to being concerned mainly about a tiny computer chip the average person doesn’t think about?

The answer to this new problem-cum-opportunity, for China at least, is a multi-pronged, multi-year strategy involving significant change designed to change the silicon chip landscape, disrupt their rivals and advance the country's own goals (for more on this see: Section 4, here ).

The truth for CEOs and boards today is that becoming a Generative AI company is the equivalent of being China in the silicon chip era. There’s plenty of other things to worry about, but there’s also a very significant pressing new factor on the horizon that may just change everything.

This challenge is compounded by the need to pivot to Generative AI as soon as possible. In the rush, there are multiple examples of businesses creating poor AI products that are destined to fail, or which already have.

This series of two articles suggests four areas of focus for CEOs who need to pivot to AI now, without endangering their core business. Everything here draws on seeing this happen first hand, working with global companies to pivot to Generative AI; a switch that can be like changing your focus from oil barrels to semiconductors.

Focus area #1: It’s always about people

People-first digital transformations within large businesses have an 80% chance of success . Transformation projects which fail to put people first have a 70% chance of failure.

Pivoting a business to Generative AI can seem like a technology project. But, like anything else within a business, it is also always a people project.

If faced with the chance of an 80% success rate or a 70% failure rate, with little context, most CEOs would make the easy choice. Yet, when it comes to digital transformations, many companies end up paying lip service to the people element, handcuffing their project from the outset.

When pivoting to Generative AI, you must start with people. There are three key questions to ask. The quicker you’re able to answer these, the faster you can pivot.

1. Where are we heading and who do we need?

McKinsey’s ‘taker, shaper, maker’ concept continues to provide a useful model for CEOs to establish what they are offering.

Takers use existing Generative AI technology, adapted to a limited degree. Shapers use the same existing AI technology, but pair it with additional data or structures to produce something new. Makers are in the market to produce genuinely new Generative AIs.

In the people sphere whether you are a taker, shaper or maker makes a big difference. If your plan is to incorporate Chat GPT, Bard (now Gemini) or another highly visible Generative AI into your offering then you will need a certain type of person. If your plan is to take on Microsoft and Google with your own in-house developed AI then you will need a completely different type of person.?

Knowing exactly where you are heading allows you to define exactly who you need along the way. The alternative is to embark on a huge general engineering talent acquisition, which is likely to be extremely expensive and unlikely to deliver the best results.

1. What is our gap to the above?

If you know where you are heading, what type of AI projects you will be involved in and who you need to deliver those projects, then you can assess your current gap to where you need to be.

This gap could be significant, but it is possible to make large leaps if you are aware of how far you need to jump.?

Digital banking payments, for example, were developed and spearheaded in the West. When Asian markets came to roll out these payments, much of the leg work had already been done and Asian banks caught up with their Western counterparts extremely quickly, to the point where Asia’s banks are now leading the digital payments revolution . That’s a huge leap forwards from the starting point and the same can be true for a company’s AI function. A big gap, once identified, does not need to remain that way for long.

1. What steps will we take now to bridge the gap?

And that’s because when you know where you are heading and your current gap you can start to create solutions to bridge the gap. Traditionally these could be hiring or upskilling, but they could also be more creative.

In a recent major partnership between two global technology companies, one company sent hundreds of employees onsite to the other to learn about how they work. This was a major step but a necessary one for the second company to advance their current efforts.

Partnering, strategic investments and other approaches can also help you to bridge your gap as quickly as possible.

Focus area #2: Products still need to solve problems - where can AI help your customers?

Last year a company with a new AI tool approached me to become an early adopter. The tool would draft your social media content for you and then schedule and post the content at the optimum time.?

On the surface this sounds good and addresses a need. Content production is time consuming and making sure you’re doing your all to get it in front of people at the right moment is something many of us are not good at or don’t have time for.

But, on closer inspection, what value was this paid-for solution delivering that couldn’t be found elsewhere, for free? Chat GPT and Gemini produce content, if you want them to. Most social media sites have built in schedulers. The ‘issue’ that was being solved here was those things not being in the same place, which doesn’t feel like it’s worth much money to me or anyone else.

Businesses are rushing to include AI in their products or make AI their product, but if you don’t have a unique value proposition then this is doomed to be a waste of time and money.

Towards the end of this year it’s likely that we will see the AI market rationalise . Consumers will quickly see through bolted-together products that add little value and offerings that are ‘quite interesting’ but nothing more will start to disappear.

For CEOs, who need to move quickly, there is a delicate balance to strike between speed and value. Try to answer the following questions.

1. Is your approach AI in the product or is AI the product? This will help to give your approach to AI clarity and focus. If AI is in your product then the newly-introduced AI element must add value to what you already had. If AI is now your product then it must operate on normal product terms; what is the unique value proposition? How does it help your customers?
2. What is the route to monetisation? Products must, eventually, make money somehow. This doesn’t always need to be obvious. Famously, Google has never charged anyone to execute a search query. But your AI product needs to make money for your company somehow and the sooner you can map this route out, the easier your product’s journey will be.
3. How can AI make solving your customer pain points better or easier? AI is not a silver bullet, but paired with great ideas it can be incredibly powerful. Your company likely already solves customer pain points to a fantastic degree. Revisit those pain points through the lens of AI. What could you make better or easier? This is a route to delivering something fantastic through AI.

Move quickly, but don’t forget the planning

China needs to move quickly to take advantage of the silicon chip opportunity and head off an economic risk. They seem to have done that, but they’ve also created a multi-pronged, long-term approach that considers multiple factors.

CEOs are being forced to move quickly with AI. If you do not then your competitors will. But moving quickly means that there will be plenty of companies who offer solutions like the social media scheduling/creating tool. Ideally, your company's AI approach will produce something more substantial.

To make sure that this happens you must have a people plan and a product plan.

When you’ve thought about your company’s approach to AI, how much time have you spent on people? Are you setting yourself up for a 70% chance of failure or an 80% chance of success? Which would you like your AI project to have?

Have you readdressed product, and customer pain points, or is your AI approach essentially ‘bolted on’? Does your AI product, or AI-enhanced product, have a genuine value proposition and, crucially, will people actually pay for it? Is it ‘quite interesting’ or a cutting edge tool for the future?

Part 2 of this series, published next week, will cover two further elements CEOs must consider when pivoting to AI if they want their business to continue to succeed.