From assistance to AI-first integration AI’s capabilities have already moved beyond just providing assistance with automated tasks. The challenges of AI implementation today focus on evolving business models to capitalise on the technology’s ability to create value. In essence, we’re in the era of AI-first integration. To understand what this looks like in action, take another of the entrepreneurs CBIT works with: a company that produces door access control, ie keypads, facial recognition and fingerprint scanners. The firm has been successful for well over a decade, but began to suffer from legacy systems that store data in different areas. Customers were demanding a modern user interface, but this would require changing the entire system. The breakthrough came from adopting a lean corp structure: small, cross-functional teams empowered by AI agents can move faster, make better decisions with shared data and continuously redesign processes, thereby turning a legacy challenge into a platform for disruption. The C-suite started using AI tools to rebuild the entire technology stack, integrate customer data for service design and create a customer GPT that salespeople and engineers could consult. This had a profound impact on the company’s structure. Every single person now has an AI agent working alongside them, enabling people to adopt multiple roles. For instance, the salesforce has now taken on an additional customer service function. The key thing to understand is that jobs are becoming more fractional. Instead of filling 100 per cent of a single role, responsibilities are allocated so that individuals are taking on 20 per cent of multiple positions at the organisation, supported by an AI ‘hive mind’ that provides quick
BIOGRAPHY Xiao Ma is professor of
entrepreneurship and management at Nottingham Business School, Nottingham Trent University and the director of the Centre for Business and Industry Transformation (CBIT). As CBIT director, he provides leadership for all centre activities, including empowering disruptive entrepreneurs through personalised education and building ventures to transform industries, as well as conducting world‑leading and high-impact research
At the same time, an increasingly fractionalised workforce encourages more localised decision-making. Some leaders will be more comfortable with this than others. Those who wish to recentralise control may opt to reinforce communication channels and update best practice guidelines. Other managers may embrace change as their responsibilities shift more towards coaching than commanding. Preparing leaders for tomorrow’s AI natives Our responsibility as business schools is not just to offer training for the current business landscape, but to anticipate future developments. Casting a glance ahead, we can see that the trend of people using AI to enhance their efficiency at work will only increase. The next generation of leaders currently studying for undergraduate or postgraduate management degrees is developing skills with a range of AI tools embedded in their courses. These AI natives will enter the workforce ready to deploy AI strategically to optimise performance. In anticipation of this new environment, CBIT is working closely with international partners to build an AI Transformation Foundry.
and efficient access to information. Because of this work, productivity has increased by around 80 per cent.
32 Ambition • ISSUE 3 • 2026
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