Why Consultancies Should Stop Trying to Become Tech Start-Ups - And What They Should Do Instead

By Robert, CEO of TheAX

Over recent months, I’ve had several conversations with consulting leaders who all share the same concern:

“We know we need to use AI, so we've hired a guy who is a whizz with AI and he's building us some stuff." and then in response to the obvious question on how its going. No, we haven't had much ROI yet. But we are keen on a strategy of building something for ourselves like the top 4 firms have done.”

But is that really a tenable strategy for most consultancies?

In response to an urgent crisis in a market where suppliers in the last 12 months have been immature with their products, many firms have taken a predictable path - building internal AI tools, launching innovation labs, spinning up prototypes, and investing heavily in internal engineering teams. It’s understandable. The market is evolving at breakneck speed, clients are demanding answers, and consultancies naturally want to lead from the front.

But a hard truth is emerging across the industry: most internal AI projects simply aren’t delivering meaningful transformation. And the data backs this up clearly.

According to the 2025 MIT NANDA State of AI in Business report, 95% of enterprise AI initiatives deliver zero measurable ROI, and only 5% of custom-built AI pilots ever reach production. Even more telling, companies attempting to build their own AI tools internally see half the success rate of those who partner with external specialists.

If we strip away the hype, one question stands out: Why do consultancies believe that becoming a tech start-up is the right route to AI transformation?

The Build-It-Yourself Trap

Internal AI initiatives almost always begin with good intentions. A team identifies an efficiency gap or a client delivery opportunity, a pilot is launched, and leadership can proudly say they’re “investing in AI”.

But evidence shows the pattern is alarmingly consistent across the industry:

• Pilots stall because tools don’t integrate into real workflows.

• Systems break because they don’t learn or adapt over time.

• Users prefer ChatGPT over internal tools because it is more reliable and more familiar - and just better UX.

• Teams underestimate the constant pace of model upgrades, new frameworks, security standards, and protocol changes.

• Internal build teams get stuck maintaining prototypes instead of delivering value.

The result? Lots of activity, very little transformation.

The research is blunt: the biggest reason AI projects fail is not regulation, not infrastructure, not even talent - it is that most systems being built internally do not learn, do not adapt, and do not integrate into day-to-day operations - but most importantly, its not the consultancies 'day-job' building innovative systems with brand new technologies - they are not AI-Tech Start-ups (even if they might like to be).

This leads to the most important statistic of all: Enterprises are twice as successful when they partner with specialist providers instead of building internally.

Consultancies Are Not Tech Start-Ups — Nor Should They Be

Consultancies exist to create value for clients, solve complex problems, and deliver expertise - not to run high-risk software R&D divisions. Yet many are now:

• hiring engineering teams,

• building proprietary tooling,

• trying to keep pace with agent architectures, memory frameworks, MCP/A2A protocols,

• and attempting to do part-time what AI vendors spend 100% of their time doing.

It’s a strategic distraction.

AI evolves faster than any previous technology cycle. Tools change monthly. Best-in-class techniques change quarterly. Entire frameworks are replaced annually.

Even well-funded internal teams cannot keep pace with a global ecosystem of dedicated AI companies innovating at industrial speed.

The result? Consultancies are sinking time, budget, and brand equity into becoming something they’re not - while still falling behind and seeing mostly very little return for their efforts.

Meanwhile, their competitors who partner with specialist AI providers are delivering real transformation to clients, winning deals, and scaling AI capability far more effectively.

The Data Shows a Better Way Forward

When you zoom out, a clear pattern emerges across the market:

1. Internal builds fail more often than external partnerships

Internal tools succeed only 33% of the time, compared with 66% for external partnerships.

2. Most AI investment goes to the wrong places

Executives allocate 50–70% of AI budgets to sales and marketing use cases — while the biggest ROI sits in back-office automation and operational delivery.

3. Users prefer consumer tools over internal builds

Even in companies with official AI programmes, 90% of employees use personal ChatGPT/Claude accounts because internal tools are too static or too brittle.

4. The real gains come when systems learn

AI systems that don’t learn from feedback or retain context don’t scale — which is why 95% of pilots never produce P&L impact.

Consultancies don’t fail due to lack of ambition — they fail because they are building in the wrong model.

This Is Where Specialist Partners Like TheAX Come In

The industry is now entering its second phase. The experimental era is ending. The transformation era is beginning.

This is now beyond playing with new technology, its serious business that needs to be done right and in 2026 we will see an inflection point for AI in consulting that all consultancies must ensure they are on the right side of if they are to secure a future.

Specialist suppliers such as TheAX have matured at exactly the moment consulting firms need help the most.

We have:

• dedicated agent frameworks

• Application building expertise in a team dedicated to building AI platforms for for consultancies

• AI architectures that learn and adapt

• client-tested delivery models

• deep understanding of how consulting operations really work

And we’ve packaged this into onboarding and implementation solutions that are easy to consume, rapid to deploy, and structured for measurable value — most notably through our AX30 Project, which delivers fast results in 30-day's through high-impact phases.  This delivers not only a Proof of Concept, but a fully operational AI-powered consultancy Product ready to sell.

No consultancy needs to “build everything” anymore. They simply need to choose the right partners.

The Strategic Choice Ahead

Consultancies today face a pivotal decision:

Option A — Build Everything Internally

• Slow

• Risky

• Expensive

• Hard to maintain

• Outpaced by market evolution

• Low likelihood of real ROI

  
  

Option B — Partner With Specialists Who Do This All Day, Every Day

• Faster delivery

• Lower risk

• Far higher success rates

• Proven toolkits

• Systems that learn and adapt

• Immediate value for teams and clients

The industry data is conclusive. The strategic logic is obvious. The market window is narrowing.

Looking Back: History Has Never Rewarded Reinventing the Wheel

Across multiple technology cycles, the organisations that insisted on building what they could have bought almost always fell behind. From the 1990s ERP wave, to CRM in the 2000s, to cloud migration in the 2010s, history shows a consistent pattern: companies that tried to develop their own platforms struggled with cost overruns, slow deployment, and technical debt - while those who partnered with specialist vendors moved faster, scaled more effectively, and outperformed their peers.

Concrete Examples from the Last Three Decades

• ERP (1990s–2000s): Many enterprises attempted to build proprietary ERP systems before SAP and Oracle became dominant. More than 70% eventually scrapped their internal systems due to spiralling cost and complexity, migrating to commercial platforms that had already solved integration, compliance, and scalability.

• CRM (2000s): Global banks and insurers famously tried to build their own CRMs. Within 5–7 years, almost all abandoned these efforts as internal builds became unmaintainable. The firms that adopted Salesforce grew their client-facing productivity far faster — benefiting from continual upgrades they could never have matched internally.

• Content Management Systems (2005–2015): Many media organisations spent millions creating bespoke CMS platforms only to later replace them with WordPress, Drupal, or commercial SaaS alternatives. Internal builds struggled to keep pace with editorial needs, security updates, mobile UX shifts, and evolving SEO standards.

• Cloud & DevOps (2010s): Countless enterprises attempted to build their own cloud orchestration or private PaaS layer before AWS, Azure, and GCP fully matured. Nearly all shut these down. Internal platforms couldn’t match the speed of cloud provider innovation — with some refreshing infrastructure monthly, not annually.

• Productivity Suites (2010s–2020s): Many organisations ran proprietary intranet or document-management tools before adopting Office 365 or Google Workspace. Once they switched, collaboration efficiency increased overnight - proving that best-in-class platforms outperform homegrown alternatives every time.

The lesson repeats: transformation has always been accelerated by adopting market-leading platforms, not recreating them internally. AI is no different - except the pace of change is even faster.

The Bottom Line, and the Path Forward

AI will not reward those who try to be everything. It will reward those who focus on outcomes, partner intelligently, and scale with speed.

Consultancies do not need to become tech start-ups - they need to become AI-enabled consulting firms.

And that is exactly what TheAX is designed to deliver.

TheAX AX30 Project - Your Fastest Path to AI Transformation

If your consultancy is ready to move beyond experimentation and start delivering measurable AI transformation — internally and to clients — the AX30 Project offers a proven, low-friction, high-impact pathway.

Let’s build the future of consulting, together. Click here to learn how to Get Started with the AX30.