1/ 90% of companies “use AI,” but 67% are still stuck in pilot mode
The issue of AI is not being able to build a wrapper or new PoC. Scaling requires good, clean, and accurate data to feed into the tool. Further, you need a sound technology architecture to make it all work and flow — mainly cloud-based.
2/ 62% of orgs are experimenting with AI agents, 23% are scaling AI agents.
Most are in tech and healthcare. Healthcare is a huge opportunity for AI agents. It is often where people feel lost or most curious, particularly in today’s digital world. We will see a stronger focus here.
3/ The impact gap is massive. 64% say AI helps innovation, but only 39% see real EBIT gains.
AI requires significant investment to scale the tech effectively. Further, it’s not just the technology that needs to change. It’s the tools, people, and processes that hang off it also, which drives up the cost.
4/ The high performers (top 6%) think bigger.
They rebuild workflows, set growth goals, and invest real budgets, not just POCs. With certain technologies the bigger the thinking, the higher the reward. If you can find pockets within the organisation to improve a process, it will compound in terms of the improvement and pay-off.
5/ Leaders who own AI personally are 3x more likely to scale it.
This is a technology that requires leadership to be part of the solution, and lean into the technology. AI is adaptable and accessible. The more invested leadership are, the harder they will push the agenda of AI.
6/ The winners use AI to transform how work gets done, not just speed it up.
We all live and experience friction in how work is done. A better process has a range of benefits from employee morale through to cost savings. The non-monetary benefits are extremely valuable to set as KPIs and measure.
7/ The average company measures efficiency.
The best ones measure how fast their agents can act. The speed of information turned into actionable insight is the new competitive advantage.
8/ Risk management is catching up with 51% having already seen AI backfire, mostly from inaccuracy.
Trust is what is holding AI back. We are seeing the growth of AI slop; on a similar note, can businesses empower AI with their most valuable decisions?
9/ The workforce impact is foggy. 32% expect cuts, 13% expect growth, everyone else is guessing.
What we typically see with the emergence of a new technology is uncertainty. Old jobs will go away where there is a clear process with predictable data flow. But new jobs will emerge, ranging from engineering, sales, through to risk and leadership.
10/ AI adoption is mainstream, but true transformation hasn’t started.
We are still away off seeing the benefits of AI come to fruition. Further, it is capital intense. Most NVIDIA chips only last 1 year before a new one will come out and supersede it. Companies need to be strategic with their investments.
Bottom, lots of activity, few results.