Why Consultants Matter More in the Age of AI

I’ve been thinking about the role of the consultant now that AI has dominated so much of the tech industry that I’ve worked in for the last five years. Every conversation, every conference and meetup, and nearly all of my LinkedIn feeds talk about the change, the shift, the restructuring, and layoffs are everywhere. I hear in these conversations that people are excited, but mostly they are anxious because there’s no real view of what the future will look like when the dust settles. With that said, I am starting to see some clarity in all the uncertainty in that there are still fundamentals that will ring true. Certain core principles of business, strategy, and human expertise remain relevant, and arguably more critical than ever. Software craftsmanship isn’t going away and will become more important as leveraging AI in the software development lifecycle becomes more normalized. Experience will never be replaced and with that the role of the experienced consultant becomes more important than ever.

The path to AI adoption is not linear, nor is it one size fits all. AI tools are often marketed as turnkey solutions; plug them in, feed them data, and let the insights flow or buy the licenses, release them to the dev teams and wait for 10x productivity gains. What a consultant brings to the table is their experience across a vast and diverse client base and equal measure of tools and approaches. While a financial institution's in-house team may have deep knowledge of their specific systems and products, consultants have a unique, panoramic view of the market and where AI solutions in many different forms have worked best.

The Power of Collective Memory

Consultants regularly implement and integrate technologies into existing systems across businesses and in vastly different working environments and architectures. This exposure allows them to identify patterns of success and failure. They know which tools genuinely streamline compliance and which are buzzwords, which tools need more guidance and skill and which are intuitive enough for out-of-the-box solutions. The mistakes one firm makes in addressing data drift can become a lesson for the next. Technology consultants and consulting firms like Ippon possess the power of collective memory, immediately steering a client away from common, time-consuming, and expensive mistakes. They recognize the "gotchas" in third-party vendor integrations, the hidden costs in specific cloud architectures, and the regulatory nuances that an internal team might overlook until an audit reveals the gap, and the same holds true for how and where to use AI. Having seen how different organizations prioritize investments, they can quickly identify high-impact use cases versus distractions. They help companies avoid spreading efforts too thin and instead focus on initiatives that align with business outcomes, regulatory constraints, and long-term goals.

One of the most common conversations I’ve had recently is about the cost of AI token usage, and as a consultant, I’ve seen how quickly those costs can grow if left unchecked. Cost control in AI isn’t just about technical expertise, it’s about strategic engagement with the tools. Successful implementations are disciplined and deliberate, knowing when to use a smaller less expensive model for simpler operations versus a more expensive one, or when better coding practices can lead to cleaner code and then require a less expensive model to help with refactoring. These are not always obvious reasons for AI token usage to grow exponentially, but these are common patterns that I’ve seen and recognized quickly. This is where the experience of a consultant holds power in the age of AI, understanding how to architect AI usage in a way that scales not just quickly but sustainably.

Learning from Failure

Success stories are valuable, but failures are often better teachers. Consultants are uniquely positioned to bring those lessons with them. We’ve seen organizations overinvest in AI without clearly defining the problem or relying too heavily on automated outputs without human oversight. In many cases, the technology works exactly as intended, but the strategy surrounding it was never clear.

I’ve personally witnessed situations in which leadership underestimated the cultural resistance to adopting new tools and spent thousands of dollars on licenses only to have the tools sit idle. What was missing was the alignment, the training programs, the metrics to decide if things were working, and a clear understanding of how and where these tools would best fit into the existing workflows. Encouraging experimentation worked well in the early days of unleashing AI into an organization, but even encouragement needs guidance and strategy. Without a strategic approach, even the best laid plans for AI adoption will never gain traction, forcing organizations to pause, reassess and all at an additional cost.

Other times, AI adoption strategies have failed because there is too much engagement. Teams move quickly to integrate AI into multiple parts of the business, only to realize later that they’ve created fragmented solutions, different tools solving overlapping problems, inconsistent outputs, and rising costs with no clear ownership. These are recurring patterns that many businesses will face as the AI revolution continues.

Perspective Over Politics

Consultants bring something that AI cannot: perspective. One of the most consistent failure points is how the problem is framed from the start. Organizations jump to solutions before clearly defining the problem they are trying to solve. AI amplifies this issue because it’s easy to generate outputs quickly, which can create a false sense of progress. Consultants help slow this down in the right way. They have allegiance to goals rather than to the internal politics of a company, which means they ask better questions, challenge assumptions, and ensure that the problem being solved is actually worth solving. That discipline is strategic, and it’s increasingly rare. In all the uncertainty that AI brings, the one thing I see that will carry many companies through is having a clear problem definition and disciplined prioritization to that goal, in other words strong strategy, and executing it with intent, and that’s what consultants do best.

If you’re navigating AI questions in your own organization, you’re not alone. The most valuable conversations I’ve seen aren’t about tools, they’re about the priorities, trade-offs, and where AI actually fits. Ippon has seen a lot in a short amount of time, and we are well positioned to help your organization, so please reach out and let's start a conversation about your AI strategy, not just the tools!