How AI is Redesigning Business Models

Artificial intelligence is often framed as a productivity story, where employees complete tasks and routine work is automated. However, a larger impact is materialising: the transformation of the business models that organisations have relied on for decades. 

Recent research suggests the real challenge is organisational reinvention. BCG’s 2026 AI at Work report found that 74% of employees now use AI regularly and 42% save the equivalent of a full working day each week. Yet most organisations are struggling to translate those gains into meaningful business value, with AI changing jobs faster than companies are redesigning their operating models.

From data governance and leadership capabilities to consulting models and professional services pricing, AI is exposing assumptions that have underpinned organisations. The question is no longer how to deploy AI, but how to redesign businesses around it.

The rise of AI-native organisations
“AI adoption is a workforce transformation, not merely a technology deployment,” highlights Seb Kirk, CEO and co-founder of GaiaLens. Rather than focusing solely on model performance, AI-native organisations invest in data readiness, governance and workforce capability as the foundations for sustainable transformation. 

Kirk argues that many businesses mistake successful GenAI demonstrations for genuine AI readiness. “The model itself is rarely the blocker; the underlying data environment is,” he says. Unclear data ownership, fragmented systems and poor data traceability appear in most AI readiness assessments, often forcing projects back into redesign before they can scale. These weaknesses create hidden business costs through duplicated work, manual validation, slower decisions and lower trust in AI outputs, while increasing compliance and reputational risks in regulated industries. Businesses are becoming – and must continue to develop as – AI-native organisations “treating data as an operational asset with clear accountability.”

When ownership sits with the people closest to business processes, supported by governance frameworks and shared standards, organisations build the trust needed to deploy AI confidently at scale. “AI is transforming the competitive advantage of businesses, not with the newest models, but with those that redesign their operating models around ownership, governance and measurable business outcomes,” Kirk concludes.

Unlocking the potential of the generalist CEO 
If AI is changing how organisations operate, it is also reshaping what leadership looks like. Most leaders rise to the top through one function. Yet as Edward Rowe, governance expert and author of The Standard Model for Business, points out, as organisations scale and the world becomes increasingly complex and interconnected, the ability to comprehend the entire system and its intricacies is becoming increasingly important. AI can be a powerful tool to build generalist CEOs and help them operate at this system level, he says.

“AI has the power to streamline the process of acquiring, translating and interpreting information across multiple disciplines,” Rowe notes. “This does not remove the need for deep technical expertise, but AI can start to close the gap between executives working across the business and functional specialists. This knowledge can then help CEOs spot patterns and build alignment organisation-wide.

“However, it’s important to note that access to knowledge does not replace human judgement and critical thinking. Leaders need to evaluate the information given by AI and know its limitations, mitigate bias and ensure accuracy. Organisations are also grounded in human relationships, which must remain a key leadership focus,” Rowe says. 

“The CEOs who thrive in the AI era will not be the deepest specialists; it will be those who understand how each function connects together. AI could make this easier when used effectively,” he concludes. 

The AI consulting paradox
The need for organisations to build internal AI capability also raises questions about the future role of consultants. AI is forcing enterprises to rethink how they create value, but it is also exposing the limits of one of the largest business models: consulting. This is the argument of organisational AI strategist Fahed Bizzari, who explains that “the real challenge of AI transformation is not deploying the technology but changing how people work.”

BCG’s latest AI at Work report found that organisations that redesigned their processes are 24 percentage points more likely to report measurable business improvements than those with limited strategic direction and access to AI tools. Bizzari argues that this proves the technology alone is not driving transformation. 

“Capabilities such as judgement, governance and new ways of working cannot be packaged into a report or installed like software. Capability forms through use.” While consultancies package AI implementation strategies, their own research shows it must go deeper than that – BCG’s 10-20-70 rule notes that 10 per cent goes to algorithms, 20 per cent to technology and the remaining 70 per cent to people and processes. 

Bizzari explains that “this creates the AI consulting paradox: businesses can buy AI strategies but they cannot outsource the organisational capability required to realise their value. This must be built from within. Businesses – and consultancies – must redesign the very AI capabilities and training they develop within their teams.”

The future of the billable hour
AI is also challenging how organisations charge for their services. Bjarne P. Tellmann, author of Law in the Era of AI and CEO of FjordStream Advisors GmbH, highlights that not only is AI making professional services, in particular, more efficient, but it is “fundamentally reshaping what the work is, how it is delivered and who is best placed to deliver it.”

“For well over a century, the billable hour has been the backbone of charging within organisations such as law firms,” Tellmann explains. “Clients pay for time. Lawyers track their hours in time-based increments, with partners profiting from the spread between what associates cost and what they bill.”

However, Tellmann elaborates that these AI systems are now beginning to complete tasks themselves, while “simultaneously, clients are becoming increasingly focused on hiring organisations to achieve outcomes, rather than to provide hours of work.”

He warns that “AI is dissolving the structural embeddedness in technology systems, reward structures, cultural norms and organisational economics. As use of agentic AI becomes more prevalent, these dynamics will shift at an accelerating rate. The result will be the emergence of strong demands for a genuinely new pricing paradigm built around outcomes, integration and value, rather than time. The question for every leader is whether their business will spearhead this transition or be led by it.”

The next AI frontier: business model reinvention
Although AI is often measured by the productivity gains it delivers, its most profound impact is on how organisations create, deliver and capture value. Success will depend on more than deploying new technology. It requires organisations to redesign operating models, strengthen leadership and governance, build internal capability and rethink long-standing commercial models.

As AI becomes embedded across every function, competitive advantage will come not from using AI to make existing ways of working more efficient, but from reimagining the business itself. The question for leaders is no longer whether to adopt AI, but whether they are prepared to transform alongside it.