London Tech Week brought together thought leaders, innovators, and policymakers to explore the dynamic landscape of artificial intelligence (AI). The event was a melting pot of ideas, spanning the intricate balance between fostering innovation and implementing effective regulations, practical advice for AI implementation, and the ethical use of AI for social good.

Balancing innovation and regulation

One of the central themes of the discussions was the nuanced relationship between AI innovation and regulation.

In a panel moderated by Simon Edward (Director, South Bank BID), speakers including Yatin Mahandru (VP Head of Public Sector and NHS, Cognizant), Zinnya del Villar (Data and Technology Director, Data-Pop Alliance), Emma Wright (Interparliamentary Forum on Emerging Technologies), and Kai Zenner (Head of Office and Digital Policy Adviser, European Parliament) highlighted that while AI presents numerous opportunities across sectors, the regulatory landscape needs careful navigation. Discussing AI in general terms is not enough; strategies must be tailored to specific use cases, and countries need to avoid generalizations when discussing AI.

Wright pointed out that regulations can sometimes stifle smaller businesses while helping larger companies solidify their market positions. A balanced, sensible approach is necessary - one that anticipates future regulatory directions and assesses risks and costs accordingly. The panel noted examples from around the globe illustrated this point: Japan’s minimal regulation contrasted against the stricter regimes of the EU, and the strategic approaches of countries like China and Brazil serve as potential roadmaps.

Mahandru also highlighted the transformative potential of AI in healthcare, with innovations such as virtual patient avatars in the Middle East providing diagnosis and treatment through generative AI. He also proposed the idea of an agile AI regulator to build trust and ensure the safe use of data, similar to financial or competition authorities.

The Future of Enterprise AI isn’t about more data - it’s about the right data

Another theme highlighted during the talks was the need for the “right data”, as opposed to sheer volume in enterprise AI. Paul O'Sullivan (SVP of Solution Engineering and UKI CTO, Salesforce) emphasized that AI's future isn't just about accumulating more data but about ensuring the quality and relevance of the data used.

In practice, this means companies need to focus on curating datasets that are not only large enough to be statistically significant but also accurate, representative, and relevant to the specific application. Without this, poor data quality can lead to issues such as AI "hallucinations" - where models generate incorrect information, potentially causing significant harm, especially in sectors like healthcare or autonomous driving.

Leadership guide for effectively implementing new AI tools

Practical advice for implementing new AI tools was shared in a session led by Claire Morris (Innovation Lead, BridgeAI, Innovate UK), Mike Turner (Global VP of Offerings: Software and Platform Engineering Service Line, Cognizant), Marni Baker Stein (Chief Content Officer, Coursera), and Joe Kaul (Group CEO, ONQOR).

They emphasized a business-challenge approach to integrating AI. Companies should focus on solving specific problems, increasing productivity in labor-intensive areas, and even, at times, pursuing radical and disruptive innovations. The panel also discussed the cultural aspect of AI integration, encouraging companies to foster an environment where research and exploration of AI’s potential benefits are prioritized.

Using AI for good

The ethical use of AI was a key focus in a panel moderated by Alban Remy (Head of Enterprise Tech & Business Services, London & Partners), with insights from Russell Goodenough (Head of AI, CGI), Katherine Platts (Global Technology Innovation, Sustainability & AI Director, Unilever), Emre Kazim (Co-Founder & Co-CEO, Holistic AI), and Irina Mirkina (AI Lead, UNICEF).

They discussed leveraging AI for social good, addressing ethical considerations, promoting transparency, and building user trust. Kazim highlighted the operational challenges of embedding ethical principles in AI processes, stressing the need for robust governance and systematic assurance. Meanwhile, Platts argued for ethical leadership from the top down to ensure AI serves societal needs equitably.

London Tech Week underscored the immense potential of AI to drive innovation across sectors while navigating the complex terrain of regulation. The event highlighted the need for tailored strategies, agile regulatory bodies, and ethical governance to harness AI's capabilities responsibly. It was inspiring to see how technology and AI are being harnessed and implemented across sectors to drive new initiatives and efforts, as well as the thought leadership across different topics.

A massive thank you to all the speakers during the day for their insight and expertise.