A technology industry veteran offers his advice for helping teams adapt and adopt in the current shift toward AI
Group Leader Eric Tumperi has been watching technology evolve in waves for more than 40 years of his career in the technology industry — and he has some lessons to share about the current wave.
His introduction to AI goes back further than most people. While working at IBM in the 1990s, he had a front-row seat to the company’s early machine learning work, including Deep Blue’s famous chess matches against human grandmasters. At that time, these were systems rooted in research projects that were built to advance computing, but the use cases for business had not emerged yet.
By the late 2010s, while attending an IBM Think conference, Tumperi saw thousands of vendors pitching machine learning solutions. By then, these products were built for large Fortune 500 companies with massive budgets to match their size — but the technology wasn’t. yet in reach for most businesses, especially not smaller, vertical market businesses like the ones that belong to the Volaris Group network of businesses.
The turning point for AI
In Tumperi’s view, the turning point for AI came the moment it became a consumer-facing product. It was a milestone for mass AI adoption when consumers were granted access to try the tools for free or for an affordable subscription fee. Within a business context, executives, programmers, and employees across the board could all try the tools themselves before ever having to wait for their IT department or a vendor.
He compares it to an earlier turning point in his career when the PC arrived on the scene for consumers. As part of a team that worked on the original IBM PC, he remembers how much of a game-changer it was to put computer power directly into people’s hands. Suddenly, people were able to use spreadsheets and word processors that had previously never been accessible for ordinary users, changing the picture of how people interacted with technology forever.
“The light bulbs were going off,” he recalls of the many use cases that consumers discovered once PCs went mainstream.
Cycles of change in technology adoption
Tumperi has lived through several eras of change in technology now. Having worked through the mainframe computing era, watching PCs spread into every business, and then leaving his secure job at IBM to start an internet company, which turned out to be the right move. Through each successive change, he’s learned how to thrive.
And he’s drawn a broader lesson from living through all these cycles. Vertical market software companies, the kind that dominate the Volaris Group portfolios, tend to be the ultimate winners when a technology shift comes along. That’s because these companies’ knowledge of their niche market gives them an edge with their customers and affords them the time to adapt and even further cater to the needs of their market.
As someone who closely watches AI advancements, he has some predictions about how AI will develop and change the way software businesses operate. First, he expects the pace of change to keep accelerating, with tools and methods used in software development changing frequently. He points to autonomous development, where AI can now be trusted to build quality software with far less human oversight than in the past. Secondly, sees an opportunity to change how companies gather ideas directly from customer-facing interactions. Salespeople and frontline stfaff could use AI tools to turn a customer’s idea into a working prototype in a short amount, making them a contributor to the company’s business development.
What leaders can do to encourage adoption
In a business context, the success of AI adoption across an entire company depend a lot on leadership.
He argues that setting an example is important for leaders. He advocates for leaders to stay curious and test their own assumptions, while also becoming heavy users of AI tools themselves. That way, there are no excuses for anyone else within the company not to adapt.
It’s not about telling others what to do, but rather, ‘Have I challenged what I believe to be true by using AI to help me learn more?’
From there, the responsibility expands from the leader to their team. He believes every employee should be given a chance to train, be mentored, and have room to experiment in their adoption journey. He has hope for slower or more hesitant adopters because he’s seen people transform their working habits in a single day once they have the right tools and a clear, supportive education about how they can be useful, and an expectation about how to use them.
