The Transformation Tradeoff
- Aug 12
- 5 min read
From the Desk of: Gina Chisholm, KellyMitchell VP of Business Operations
Technology has always moved quickly. What feels different today is the gap between the pace of innovation and an organization’s ability to absorb it.
IBM’s 2026 Tech Leader Study describes enterprise technology foundations as having been built for a slower, more predictable environment. In the same research, 70% of technology executives said teams across the business are deploying technology faster than IT can track, and only 11% said they felt fully prepared for the scale of AI agent deployment expected over the next year.¹
I see the impact of that gap in conversations all the time. Leaders know they need to move, but the decision is rarely as simple as choosing the newest technology. Increasingly, the question is: Do we move quickly to modernize what we have, or slow down long enough to reimagine how the work should be done?
There is no universal answer. But after sitting in countless rooms where leaders are making some version of this decision, I believe the right path usually comes down to three things: readiness, resources and return.
1. Readiness: How Much Change Can You Actually Absorb?
There is a natural tendency during a major technology investment to say, “If we’re going to do this, let’s do it right.” But “right” looks different for every organization.
I’ve been part of readiness exercises where we’ve brought board members, business executives, technology leaders and the people actually doing the work into the conversation. We assess technology and business readiness of course, but on most days one of my favorite things to evaluate is resource readiness. Those conversations are often where the most interesting part of transformation happens.
Everyone enters the room with a different lens. Someone sees enormous potential in what the new technology could do. Someone else knows exactly why an existing process works the way it does. Others may be protective of work they have owned for years or understandably hesitant about changing how they do their jobs. I’ve even seen something as personal as an unknown upcoming retirement influence a recommendation about a company’s future state.
None of those perspectives are inherently right or wrong. They are inputs. The work is understanding them alongside what the organization is realistically capable of absorbing and then designing the right path forward. Balancing them all out is an art - Sometimes that means significant transformation now. Sometimes it means getting the right foundation in place and intentionally coming back for the next phase.
But inherently, the most transformational option isn’t automatically the best one. The organization has to be ready for the transformation, too.
2. Resources: Can You Actually Execute It?
Even when an organization knows what it wants to change, there is a second question: Who is going to do the work?
This is another pattern I see constantly. The organization doesn’t lack ideas. Usually, it has plenty. The problem is that the same people who need to rethink the work also have day jobs.
Transformation requires discovery, process design, requirements, data readiness, implementation, project management and change management - while customers still need to be served and the business still needs to run.
And technology is creating new skill requirements at the same time. Gartner found that 77% of CEOs believe AI is ushering in a new business era, yet only 44% considered their CIOs “AI-savvy.” CEOs identified the inability to hire enough skilled people as one of the top two factors limiting AI deployment.²
That doesn’t mean internal teams aren’t capable. It means the capabilities organizations need are changing incredibly quickly.
I’ve watched the best plans emerge when companies are honest about this. They identify the superpowers already sitting inside the organization, protect the institutional knowledge they can’t afford to lose, and then determine where they need additional capacity or expertise.
Sometimes that’s one specialized person. Sometimes it’s fractional expertise for a particular phase. Sometimes it’s an entire project team. And often, it’s a mix of all of the above at different points in time – which takes incredible planning and puts an extra burden on the existing resources for adaptability and on the budget sheet.
A transformation strategy is only as viable as the organization’s ability to execute it.
3. Return: Can You Make the Investment Case?
Then comes the financial reality: transformation isn’t cheap.
And this may be where today’s technology decisions get particularly difficult.
IBM’s 2025 CEO Study found that 64% of CEOs said the risk of falling behind drives their organizations to invest in some technologies before they have a clear understanding of the value those investments will create. At the same time, only 25% of AI initiatives had delivered their expected ROI.³
That’s a difficult position for any leadership team: we can’t afford to fall behind, but we also can’t afford to invest without understanding the return.
I’ve been in these conversations, too, and the hardest part is often that some of the return is invisible - at least initially. Boards need to know how every investment impacts their shareholder dollars.
If better technology allows 100 employees to accomplish what eventually would have required 120, there is value in the 20 hires the organization may never need to make. If automation gives employees hours back each week, there is value in what they can now spend those hours doing. If better systems allow a company to respond to customers faster, make smarter decisions or scale into new markets, there may ultimately be revenue attached to that investment.
But those benefits don’t always appear neatly in next year’s budget.
Research suggests companies are already thinking more broadly about how they measure technology returns. In an IBM-commissioned study of more than 2,400 IT decision-makers, faster software development, faster innovation and productivity/time savings all ranked ahead of hard-dollar savings as the most important metrics used to calculate AI ROI.⁴
There’s another wrinkle in the AI investment case: increasingly, the cost itself is fluid. Enterprise technology purchasing has evolved from traditional software licensing to predictable subscription models and now, with AI, toward token- and consumption-based pricing where the meter keeps running based on usage. In some cases, the more successfully a tool is adopted, the more it costs. That creates a new challenge for operators and boards: how do you budget for an inherently variable expense, and continually prove that increased consumption is translating into increased business value?
The business case therefore has to ask more than “What will this save us next year?” It should also ask: “What will this allow us to do over the next five?” And, increasingly, “How will we know when greater consumption is creating enough value to justify greater cost?”
Finding the Right Transformation
This is why I don’t believe there is a formula for the perfect transformation.
I’ve watched sound plans emerge from some pretty messy conversations. They rarely represent everything everyone in the room originally wanted. Instead, they utilize the superpowers of internal talent, account honestly for budget and bandwidth, layer in outside expertise where it creates value, and prioritize the changes that matter most.
The result isn’t necessarily maximum transformation.
It’s the right transformation for that organization - at the right time, with the right resources and a return the business can defend.
And if you find yourself sitting in a room having this exact debate, call us.
At KellyMitchell, we work alongside organizations to understand where they are, where they want to go and what stands between the two — whether that means specialized expertise, fractional support, additional capacity or a full project team.
You don’t need to have the answer before you call us. Sometimes figuring out the right answer is where the work begins.
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2. Gartner, “Gartner Survey Reveals That CEOs Believe Their Executive Teams Lack AI Savviness,” May 6, 2025.
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