We’ve reached the inflection point with AI. The technology has proven itself. Microsoft, AWS, and Google solutions are securely available and can be tailored for specific businesses. Yet 88% of AI pilot projects still fail to reach production, and recent research shows that 95% of organizations get zero return on their AI investment.
The gap isn’t technical anymore.
Organizations have focused on AI disablement—building rules, policies, and guardrails. They’ve done the minimum: the rule-making. But they haven’t leveraged AI to solve actual business problems, free up bottlenecks, or make more money. Most businesses are still dabbling. It isn’t giving them a commercial advantage.
The winners in 2026 are those who treat AI as a growth engine, not a compliance exercise.
The Self-Training Strategy Is Failing
To keep costs low, businesses have relied on internal people to self-train and make it up as they go—while also doing their day job.
Guess what? They failed.
They haven’t had time or the skills to truly leverage AI to solve live business problems or bottlenecks. The result: minimum progress. Only 26% of companies have built the capabilities to move beyond pilots and generate real value from AI.
The missing skill isn’t technical or strategic. It’s innovation—the ability to approach things differently with a beginner’s mindset.
If you started today, without all the legacy, with the current tech—what would you do? It most certainly wouldn’t be what was set up 10 years ago. Sometimes we need to cannibalize our business before someone else does. Sometimes we need to change people’s day jobs. Sometimes we need to start again.
Pilots That Actually Deliver Value
The difference between dabbling and delivering comes down to one thing: pilots should be version 1 and deliver value in the first iteration.
Perhaps it solves 20% of the problem, perhaps 80%. But create a version 1 that adds value immediately. Then evolve it over time.
Start with the area where you have the most manual effort. Usually, it’s also the place where you have the most errors—manual processes mean manual errors. Map out the current process. Automate the easiest part and see how much time it saves. Then automate another part.
Organizations implementing this approach are seeing 6-10x productivity improvements by automating manual processes. That means they can grow with the same number of people.
But here’s what matters more: they’re growing faster. They can onboard or serve more customers, so now they can ramp up sales and marketing to win more customers. The people remain the same, but revenue increases with the same cost base.
That’s the dream. And that’s what AI-powered automation can deliver.
Reframing the ROI Conversation
The real opportunity isn’t cost reduction. It’s revenue expansion with fixed costs.
Yet 61% of CEOs say they’re under increasing pressure to show returns on their AI investments in 2026. They’re focused on cost of investment and this year’s budget and this year’s P&L—not seeing AI as an investment to increase future revenue and profit.
AI investments need a ROI calculation upfront done in two ways:
First, calculate the ROI for that AI project—showing the short-term cost implication versus long-term revenue and profit benefit.
Second, calculate the ROI on the cost of doing nothing and not using AI—showing the short-term cost saving but long-term cost impacts.
The costs of not automating using AI mean a proportional increase in resource cost as you grow, resulting in flat profit margins. The costs of not innovating using AI mean lost commercial opportunities, not winning new clients, not winning awards, and then losing clients over time.
It’s a double hit: margin compression from linear cost growth plus market share erosion from falling behind on innovation.
What Customers Actually See
Customers make buying decisions by comparing their options and trialing them. If competitors offer better solutions that are more innovative or easier to buy, customers will choose them.
The customer experience difference is real. Companies with high AI exposure show 3x higher revenue growth per worker compared to slower adopters. Industries that have embraced AI see labor productivity grow 4.8 times faster than the global average.
This gap is becoming impossible to close without fundamental changes.
The Leaders Who Are Winning
The C-suite leaders who are actually winning are doing something different.
They’re making a clear statement to their boards and teams that they are focused on leveraging AI to grow the business—to automate and innovate. This is the step change, now that the technology has proven itself.
But a declaration without action means nothing.
Once a leader makes that statement, the very first action separating declaration from actual transformation is this:
Create a roadmap starting with automating the biggest bottleneck first. Create an AI playbook to make it easy for all staff to use AI in line with the business rules and values. Upskill people. Bring in experts to augment and fast-track the in-house team.
Sometimes you need external people to challenge you. Start with a pilot or prototype. Test it. Prove it or disprove it. Help your people understand that by freeing themselves they can get rid of all the admin and have much more fun jobs.
Or sometimes you need to get comfortable with being uncomfortable and let people go. It will vary by business.
The New Benchmark for 2026
The priority that separates true leaders from those who just followed the playbook is this:
Prove that you can make a 10x productivity improvement by solving a bottleneck within 4 weeks.
Not in six months. Not after a year-long implementation. In four weeks.
The organizations that can demonstrate this speed and impact will have mastered what others are still theorizing about. They’ll have moved from defensive posture—making rules and checking boxes—to offensive strategy—using AI to solve their biggest problems fast.
The technology is ready. The question is whether your organization is.