From the doctor’s waiting room to the boardroom, AI is everywhere. But what is your company’s AI strategy?
If you’re reading this post, you’ve probably already scrolled through dozens of AI-related posts and headlines. For the first time in my nearly two decades working on data and AI, I have found myself in the middle of AI discussions with other parents at school drop-off, at my annual doctor checkup and with my wife over dinner. Without question, generative AI — or AI that can generate original content such as text and images based on user prompts — has gone mainstream, and this must be what peak AI feels like. Not surprisingly, I’ve been inundated by clients and CIOs asking me what generative AI means for the future of their business and how to explain the technology and its implications to their CEO and board.
But first, why is there this sudden AI fever pitch? This isn’t the result of a radical new approach to AI from two months ago. Far from it, in fact. While the origins of AI can be traced back to the mid-1950s, three key drivers are converging and fueling the current breakthroughs:
- We reached an inflection point with what large models can do. As outlined by the authors of the Stanford University paper “Examining Emergent Abilities in Large Language Models,” a new paradigm has evolved from task-specific models, trained to do a single task, to task-general models, which can perform many tasks. New abilities (and likely risks) have recently emerged as more and more data are used to build models.
- ChatGPT has contributed to democratizing AI in several ways. ChatGPT is available and accessible for free on the internet, which reduces many barriers to entry for those who want to learn about AI or use it for projects. Prior to ChatGPT, AI use was primarily limited to data scientists with years of coding experience. Now, since there are no resources required to train this AI tool, students, teachers and anyone with an internet connection can leverage it. AI is no longer a spectator sport or a tool that requires an engineering or science degree.
- AI funding in the last few years has skyrocketed. Global AI startup funding reached a new record of US$66.8 billion in 2021, up 108% year over year, according to CB Insights. The number of AI M&A deals was up 96% globally, and there were a record number of IPOs, according to the report. And the International Data Corporation (IDC) predicts global spending on AI will surpass US$300 billion in 2026. We’ve already seen multibillion-dollar investments in AI in this first quarter, and the trend is likely to continue as the functionality becomes increasingly important across a wide range of global industries.
The pressing question is to go beyond the shiny object: how can corporations harness the power of generative AI and other forms of AI to transform their business models or their operating models?
I recently had a conversation with an executive of a large publicly traded corporation and a self-proclaimed avid Midjourney and ChatGPT user. Of the nearly 100 million monthly active users, it’s likely that he isn’t the only C-suite executive experimenting with ChatGPT. The more the C-suite and boards experiment with this technology, the more pressure it puts on leaders to have a plan. What are their expectations for the companies they direct? Do you know how to respond?
As Jeff Wong, EY Global Chief Innovation Officer, told The Wall Street Journal, CIOs should be experimenting with ChatGPT to determine how it could best be put to use, mostly through trial and error. While there are limitations and potential biases, exploring how to implement an AI strategy, including generative AI, for your business now is crucial. ChatGPT and DALL-E 2 dominate headlines, but there are hundreds of startups building on top of these foundation models, and the list is expanding by the day.
EY is committed to the responsible implementation of AI systems and to help our clients shape thoughtful strategies so that they can perform better, faster and more efficiently. We are advising executives how to start with their AI strategy in preparation for inevitable questions from their CEO, board and other stakeholders. We have developed a six-week strategy sprint to help identify the opportunities and priorities, risks, roadmap and governance structure. We are focused on an outcome that is a business strategy – not a list of proofs of concept.
To move forward, especially in a time where AI headlines quickly shift from fascination to fear (and in some cases rightly so), it’s critical that organizations have a strong, trusted foundation on how and where they integrate AI. It’s also crucial in terms of how they evaluate whether it is performing ethically. A business plan starts with how AI will transform the business or operating model, establishes a plan to keep humans involved, evaluates multiple AI options (not just those in the headlines), and manages expectations on what needs to be true —all to give CIOs and C-suite leaders a viable path to AI maturity. Amid all the hype, one thing is certain: we are at an inflection point with AI. Corporate and governance leaders must be thoughtful and proactive about how they take advantage of this evolving capability to solve problems and seize game-changing opportunities.
The views expressed by the author are his own and not necessarily those of Ernst & Young LLP or other members of the global EY organization.