AI implementation without planning will only highlight ‘bad consulting’

According to Kyle Hauptfleisch, AI won’t save bad consulting; it will expose it. The chief growth officer at Daemon explains that the next 12-24 months will split firms that redesign how work is done, from those that just add tools to antiquated workflows.

AI isn’t just another shiny tool to be added to your consultancy toolkit, it fundamentally changes how work is done, from discovery to delivery. The firms that understand the distinction between AI-first and AI-added approaches won’t just survive the current disruption but define what comes next for the industry. Those that don’t risk not just falling behind but becoming irrelevant in an industry where client expectations around value delivery are higher than ever.

True AI transformation demands more than surface-level adoption. It means rebuilding processes, investing in people and platforms, and being explicit about where humans own judgement and accountability.

AI-first vs AI-added

The distinction between AI-first and AI-added isn’t semantic; it’s operational. AI-added means taking your current processes around information gathering, coding and delivery and simply bolting AI tools on. It’s the equivalent of adding an engine to an unmodified bicycle. It will move faster but preserves the same bottlenecks, risks, and ownership gaps.

AI-first, on the other hand, is a motorbike. Every component, system and workflow should be reimagined with AI at its core to improve the entire process. The expertise moves from creation to specification, evaluation, and sign-off, which makes real domain experience more important than ever.

When consultants work with clients through an AI-first lens, they’re not just accelerating existing workflows but redesigning how work gets done from whiteboard to production. The goal isn’t to make mediocre processes faster but to create new ways of working that unlock genuine, sustained value. 

The training gap crisis

Some of the bigger firms’ recent attempts to swap graduate work for AI learn the wrong lesson: tools without apprenticeship hollow out tomorrow’s talent and today’s accountability.

Companies unwilling to invest in graduates are eliminating their talent pipeline. Remove junior paths and you remove future seniors.

This short-term thinking reveals a superficial understanding of how to implement AI effectively within a consultancy environment. A “tool first, process later” approach is an anti-pattern. Without structured upskilling, evaluation, and governance, organisations will just burn cash faster.

The fundamental issue is that while AI excels at turning data into information, there is no entity that is actually thinking, meaning there is no one to take accountability. A podcast I listened to shared a perfect analogy recently. AI would be able to tell you which deck to stand on and at what time to have the highest chance of being saved on a sinking Titanic, but no model thinks the Titanic is sinking in the first place. Models execute a target brilliantly but won’t decide what the target should be or own the consequences. 

This context gap is crucial in consultancy work. AI is more like a brilliant intern than a seasoned partner, requiring guidance, context and the uniquely human ability to read between the lines of what clients actually need. Our ability to provide genuinely relevant, effective and realistic recommendations depends on understanding the broader context of client situations — and clients themselves — something AI simply cannot do (yet).

As one of our engineers puts it: "Engineering stops when coding starts." Engineering is about problem-solving and understanding systems. Coding is about production and implementation. AI leads production but humans own problem framing, trade-offs, and approvals. 

Poorly trained employees struggling with powerful tools will create a vicious cycle where the lack of integration and training costs companies more time and money – the very problems AI was supposed to solve.

True AI transformation isn’t about replacing people but using it as an augmentation tool to reimagine how people work. The consultancies that survive the age of AI will be those that can prove they create more value when it comes to AI implementation, not just move faster.

Rather, keep the graduate pipeline but redesign it. Call it Apprenticeship 2.0 and fold in supervised pairing with coding models, rotation through the development lifecycle, and reviews tied to the same outcome metrics that clients care about.

Outcome-based delivery matters more than ever  

The stakes couldn’t be higher for the consulting industry. According to Source Global Research, only 49% of clients think the value they get from consulting projects exceeds the fees paid. This should be a wake-up call for every boardroom across the sector.

AI has the potential to either solve this value crisis or accelerate it, and the difference lies in how consultancies approach AI transformation.  

Poorly implemented AI projects don’t just waste money – they waste it at unprecedented speed and scale. When you combine expensive AI tools with inadequate training and surface-level implementation, you create a perfect storm of inefficiency. AI is, after all, (mostly) an indiscriminate amplifier.

This is why consultancies must move beyond the "AI for AI’s sake" mentality. Every AI implementation or project should be laser-focused on specific business objectives, with clear metrics for success. It’s about having the right conversations with clients, ensuring every AI initiative is aligned with their business goals.

This can only be achieved if AI has been implemented into processes from the beginning, rather than retrofitted onto existing ones. You can’t bolt AI onto broken processes and expect true transformation; you need to rebuild with AI-first principles as your foundation.

The future of the consultancy landscape

Either we redesign now or keep papering over cracks.

The consultancies that thrive in the next decade will be those that invest in both AI capabilities and human talent, recognising that the magic happens when these elements work in harmony. They’ll be the firms that understand AI-first principles and can guide clients through genuine transformation, not just tool adoption, knowing that on the other side lies not just efficiency, but entirely new possibilities for value creation. The winners will have invested in platforms and people, and prove outcomes with metrics not slides.

This is rebuild time not retrofit time. The question isn’t if AI transforms consulting, it’s who leads that transformation.