Kamales Lardi, a globally recognised expert in digital transformation, has published a guide to the real-world potential of artificial intelligence in business. Her latest book, Artificial Intelligence for Business: Harness AI for Value, Growth and Innovation, draws on her experience advising multinational firms across Europe, Asia and Africa. It emphasises the importance of balancing people, processes and tools in any transformation effort. Lardi was driven to write the book by the rapid uptake of AI, which she says has generated both hype and confusion among business leaders. While AI research dates back to the 1950s, its recent leap in accessibility and capabilities has made it a pervasive force across industries. Lardi’s goal is to cut through the noise, helping leaders distinguish practical use cases from speculation, and offering clear advice on ethics, governance and the future of work.
She describes the pace of AI development as an “existential” shift—one that, unlike earlier tech revolutions, is reshaping how we live and work at a fundamental level. The convergence of AI with technologies like blockchain, augmented reality and the Internet of Things, she says, is accelerating this transformation across sectors.
Lardi highlights wide variation in AI adoption rates. Healthcare, technology, media, telecommunications and manufacturing are leading the way. Financial services, energy, consumer goods and retail are slower to move, often due to regulatory hurdles and trust concerns. She urges a value-first mindset: companies should start with their specific challenges, then explore how AI can help—supported by strong data strategies, process improvements, governance and workforce training.
A central theme in her work is human-centred AI adoption. Lardi argues that AI should augment, not replace, human capabilities. Creating psychological safety and involving employees in AI implementation leads to more sustainable outcomes. Transparency about AI’s role and openness to employee feedback are vital to reduce fear and resistance.
Leadership, she says, is key. Executives must develop AI literacy to guide their organisations responsibly. Workforce development should begin with skills gap analysis and extend to continuous learning and “sandbox” environments where staff can test AI tools within safe parameters.
Ethical governance is another cornerstone of Lardi’s approach. She urges companies to go beyond compliance and consider the broader social impact of AI. Inclusive growth strategies must ensure that all communities, especially marginalised groups, benefit from AI’s promise. She warns that unchecked profit motives risk deepening inequality and stifling innovation.
Lardi sees a growing role for public-private collaboration in preparing workers for an AI-driven economy. She supports occupational restoration schemes aligned with national skills frameworks, provided they remain focused on people rather than productivity alone.
On regulation, she praises the EU’s AI Act for its risk-based, phased structure, but cautions that complex compliance demands could favour big tech firms and suppress smaller innovators. Ethical accountability, she argues, must not become a casualty of scale.
Lardi’s clear-eyed, human-first approach offers a roadmap for UK leaders looking to integrate AI effectively. By combining technological progress with ethical governance, workforce empowerment and inclusive planning, she believes the UK can build a truly sustainable AI ecosystem.
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