The Fear Factor in AI and Automation

At a time when there’s growing pressure to modernize, there are also fears of job loss. 

“There’s healthy skepticism. People are asking: will this tool support our workforce or replace it? You can use AI to augment, replace, supplement, or downsize. The intent matters more than the tool itself.” 

Rather than jumping into technology-led transformation, Chris advocates for purpose-led exploration. “Start with the business challenge. Understand the customer environment. Only then can you determine whether AI – or any other tool – makes sense in context.” 

“You don’t lead with the platform – you start with the people. No amount of technical transformation will matter if the people using it are resistant or unprepared for it.” 

Whether it’s improving service management or scaling up for M&A integration, the starting point is user engagement. “Business transformation is inherently a people-focused endeavor; building tools just to be tools is pointless if there’s no engagement from the people who use them. The best solution is one that actually gets used. A Ferrari in the garage is useless if no one knows how – or wants – to drive it.” 

This people-first philosophy helps address systemic blind spots. Instead of playing “whack-a-mole” with surface issues, a people-first focus helps you zoom out and spot patterns you may not even know exist, allowing you to maximize both the value and effectiveness of your investment.

AI tools are a fantastic accelerator of value, but, as Chris describes, there’s a lot of skepticism and nervousness in the environment, especially regarding data security, role retention, and environmental impact. “People are concerned that AI tools are going to lead to inevitable job losses,” Chris explains. 

“But the reality is that for most businesses, the real value of AI is in removing repeatable and often time-consuming menial tasks and freeing up staff for higher value work. And fully integrated AI tools require a monumental amount of preparation, data cleansing, and foundational work that just can’t be done without the inputs and effort of the people in those roles right now.” 

Misalignment on What’s Really Needed

One of the most common pitfalls for organizations is misalignment between business need and technical ask. “You’ll see a tender for a software module, but what’s really needed is a re-evaluation of the operating model that uses it.” By reframing conversations around core problems instead of isolated tools, organizations can avoid expensive fixes that don’t move the needle. 

This shift requires a mindset change from solution hunting to problem mapping. “You’re not just solving what hurts now; you’re preventing what might fail later,” Chris explains. That longer-term view is critical in sectors like government, where legacy systems and procurement cycles often lag behind business realities. 

Chris describes a recent client engagement where a clunky service portal was the visible issue – but deeper analysis uncovered years of deferred IT investment, siloed acquisitions, and inconsistent ownership. 

“The client needed to connect tech modernization to business impact and create long-term resilience, scalability, and process alignment. They were focused on the short-term pain, without considering or planning for the long-term implications, and we were able to refocus the outcomes. What would have inevitably been another problem in 6-12 months, we were able to plan and build for now.” 

Building a Culture of Continuous Calibration 

“It’s not about locking into a five-year plan. It’s about balancing short-term fixes with long-term issues and having the flexibility to reorient when new risks or opportunities emerge,” says Chris.

He points to scenario planning, lightweight experimentation, and active stakeholder engagement as underused tools for building adaptability. “If you involve the people closest to the pain points, you’ll uncover smarter, faster, and often cheaper paths forward.”

When clients slow down to define their real problems, challenge their assumptions, and engage authentically with stakeholders, transformation becomes less risky and more rewarding. This is as true today, with the focus on AI tools, as it was in the migration to SaaS frameworks, or from centralized mainframes to distributed servers before that.

“Good tools are important,” Chris says, “but real impact comes from asking better questions, and sticking around long enough to help answer them. We live in a fast-paced, ever-changing technology landscape, and by all means, I encourage people to investigate the new and exciting technology trends. But never lose sight of the business outcomes they are there to improve.”

If you are interested in getting to the heart of your transformation issues, contact us. 

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