In 2026, the biggest names in AI lined up to go public. OpenAI, Anthropic, and others are heading for the stock market, in what could be one of the largest runs of tech listings in years. (covered by IG)
That tells you something simple. AI has stopped being a research project. It is now a business engine, and investors want to see the returns.
So the real question for leaders has changed. It is no longer “which model is best?” It is “who turns AI into a business that wins?”
If you are booking an AI keynote speaker 2026 for a conference or a leadership team, that is the shift worth understanding. I am Mark Kelly. I founded AI Ireland and the AI Awards, and my team has now reviewed more than 1,000 real AI projects. From that seat, the pattern is clear. The winners are not the ones with the cleverest tools. They are the ones who put AI to work where it changes the numbers.
The Real AI Story Has Changed
For years, AI was a technology story. Today it is a business story.
Two questions sit under almost every headline. Who turns raw AI capability into real revenue. And who actually changes how their company runs, not just how it demos. Leaders who track both make sharper calls. Leaders who chase benchmark scores keep backing the wrong thing.
The Race to Turn AI Into Money
The market is splitting into two layers. Above, the providers who build the core models. Below, the companies that bend those models around their own workflows, products, and services.
This is why the IPO race matters more than it looks. OpenAI confirmed a confidential filing for a public listing in 2026, a late-year debut is widely expected, and Anthropic is lining up its own. AI has crossed from a research story into a stock-market story. The questions in the boardroom have changed with it. Not “how clever is the model,” but “where is the revenue, the margin, and the moat.”
Microsoft has been blunt about it. The money may not sit in the model at all. It may sit in everything stacked around it, the tools, the distribution, the integration people lean on every day. On that view, the best model does not win. The best business system does.
Don’t Bet Everything on One Model
Here is a risk that hides in plain sight. Models change. They get updated, repriced, or retired, and the terms shift over time. If your whole operation rests on one model with no fallback, you are carrying more risk than you think.
Treat model choice like any serious vendor decision. Read the terms. Check how your data is handled and where it sits. Keep a backup option so a single change cannot stall your work. This is not about fear. It is about not building your house on one supplier.
Who Keeps the Value
So who ends up ahead, the model makers or the firms using them? Both, but not in the same way and not on the same clock.
Model makers cash in early. They have the brand, the scale, and the subscriptions. Enterprises win later, and they win bigger, by wiring AI so deep into how they run that no rival can copy it with a credit card.
Which gives you one rule worth keeping. Forget “use AI everywhere.” Aim for “use AI where it changes the economics.” Find the few workflows where it cuts cycle time, sharpens a decision, or opens a new line of revenue. Prove it there first. Then scale what works.
What Business Leaders Should Do Now
Skip the hype cycle. Build on three things that hold up either way.
- AI value lands unevenly across model makers, platforms, and the firms that deploy them.
- Your edge comes from execution and integration, not from owning the newest model for a fortnight.
- Pilots are not progress. The winners build an operating model around AI and stop running science fairs.
Make it a team sport. Procurement, IT, security, and the business all need to be in the room when you choose tools and decide how to use them. I see this split constantly. Across 1,000-plus projects at the AI Awards, the gap between firms that tinker and firms that build a system is stark, and it widens every quarter. That is the line I help teams cross in my executive AI workshops.
What This Means for Choosing an AI Keynote Speaker 2026
Your audience has heard the hype. What they are missing is someone who can join the dots between where AI makes money and how to actually deliver it, then tell them what to do on Monday.
That is the job I do on stage. As an AI keynote speaker, I bring:
- A founder’s view from building AI Ireland and the AI Awards.
- Hard evidence from more than 1,000 real AI projects.
- 300-plus keynotes delivered and over 10,000 leaders trained.
- Plain English, no jargon, and a short list of moves your team can act on.
The aim is not applause. It is a room that leaves with a clearer read on the AI shift and a few decisions worth making. You can read more about my work.
Frequently Asked Questions
What is the biggest AI shift leaders should watch in 2026?
AI has moved from a research story to a business one. The money question now beats the model question. Watch where AI changes the economics of your business, not which model tops a benchmark.
Will AI value go to model makers or to enterprises?
Both, on different timelines. Model makers capture value early through scale and subscriptions. Enterprises capture it for longer by building AI into workflows that are hard to copy.
How can a business reduce its AI risk?
Treat model choice like any vendor decision. Check the terms and your data handling, and keep a backup model so one change cannot stop your work.
What should I look for in an AI keynote speaker?
Experience, proof, and clarity. Someone who has seen plenty of AI projects up close, can explain the trade-offs in plain English, and hands your team clear next steps.
The Bottom Line
AI has outgrown the “pilot project” label. It is becoming a business engine, and the winners will build an operating model around it, not run a few trials and call it a strategy.
Want your audience to leave with that clarity and a plan they can use? Book Mark Kelly, AI keynote speaker 2026, for your event. Get in touch here.
