We are closing in on three years since the launch of ChatGPT, a pivotal moment in the history of technology, arguably more transformative than the dawn of the personal computer or the internet.
In just 36 months, artificial intelligence has gone from something wondrous and baffling to a business imperative. For countries, corporations, and individuals, engagement with AI is not optional; it is essential. The alternative? Lost productivity, a lack of employee engagement, or even organizational extinction.
Globally, hundreds of billions of dollars in corporate and venture funds are flowing into the AI ecosystem. Locally, Central Ohio is hosting three separate AI conferences this month alone.
It’s a logical time to ask: Where are we now? What have we learned? And where are we going?
What We've Learned from the First Phase of AI
The early history of the AI Age echoes previous technology cycles. The initial frenzy has now collided with the reality that it is tough to change how people and organizations operate daily.
Case in point: A recent MIT study finds that 95% of generative AI pilot projects have failed to deliver expected results. The reasons are timeless: unclear or absent goals, starting with tools instead of strategy, a lack of a single leader voice with ownership of the AI initiative, and failing to address users’ reasonable fears that they might be innovating themselves directly to the unemployment line.
Yet that same study reveals a less quoted but equally important finding: real people are using their own AI every day, not only to plan trips or recipes, but to re-engineer their jobs. The “shadow AI economy” is booming, often without the knowledge or approval of the IT department.
Change is happening organically through millions of small, daily experiments aimed to speed up, trim, and economize routine tasks. Yet for all the benefits, AI is still a long way from doing work that requires judgment, nuance, and intuition.
So how do we close the gap between individual action and leadership’s goal of achieving enterprise-wide impact? How can we empower people while also protecting sensitive organizational data?
By doing what we know, we make any change stick.
Avaap Pathways: Turning Strategy into Action
Avaap’s new AI Pathways leverages proven change management methodologies to help organizations cut through the noise to define a vision, assess technical and people readiness, and take the confident first steps towards meaningful, measurable AI adoption. It works especially well when you connect with those eager, secret early adopters who can champion your AI change.
The first phase of the AI Age is ending. Success in the next phase will require drawing on what we know helps people–and organizations–change.