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"Asking the right question is the key to identifying a transformation opportunity."

Paul Henninger, Head of Connected Technology, KPMG in the UK, and Head of Global Lighthouse, talks about harnessing the power of emerging technologies, including AI, intelligent automation, machine learning and data & analytics.

Tell us more about your dual roles, and how you use emerging technologies to help solve clients’ challenges?

Paul Henninger: As Head of the Connected Technology team at KPMG in the UK, my role involves leading our multidisciplinary group of about 4,200 colleagues working in the UK, Malta and India across the areas of technology advisory, cloud and application engineering, automation, and our enterprise platforms.

I also lead Global Lighthouse, the KPMG center of excellence for emerging technologies, which brings together more than 15,000 professionals across the global organization of KPMG member firms, working in different specialisms like data & analytics, AI and intelligent automation.

For me, these roles are closely connected, since both are directed towards problem solving with technology. Asking the right question is the key to identifying a transformation opportunity. Technology can be the answer, but we always start with understanding clients’ challenges.

Do you see commonalties between client challenges and if so, how do you apply the learnings?

Paul Henninger: KPMG professionals help clients with a spectrum of challenges, and often they share common features. For example, one project might involve working to transform the customer experience pathway for a banking client. Elsewhere, we’d be designing a technology solution to help a Finance department automate large blocks of manual processes. In another project, we’d be advising and delivering on the implementation of an enterprise platform with one or more of KPMG’s alliance partners, which requires connecting multiple systems in the cloud.

In all cases, KPMG professionals start with the end goal. This is where KPMG sector teams can bring their expertise to bear; we systematize and share lessons learned elsewhere. For instance, an experience from the healthcare sector in designing vaccination programs can be transferred to a project around the optimization of a supply chain for a retail organization.

On the surface these challenges from retail and healthcare may not look similar, but the underlying challenges are essentially the same, making the lessons learned extremely relevant.

What makes the difference in bringing about large-scale, lasting business transformation?

Paul Henninger: Diversity of disciplines and specialisms is key. I think about my own career, which started as an architect. I liked how architecture involved engineering, technology, design, philosophy and other disciplines to shape a powerful end product for a client. In my work, data was critical to making a building user-friendly and enjoyable.

That started my journey into data and analytics, and to take up technology roles where I started leading large teams. Very quickly, it became apparent to me that a team’s problem-solving ability is massively increased by the diversity of the contributors.

Different perspectives lead to transformative approaches. For me, KPMG embodies this philosophy. KPMG professionals have so many specialisms to draw upon to help solve almost any client problem.

Paul Henninger
Paul Henninger

What role does generative AI play in transformations?

Paul Henninger: Generative AI models can automate and execute certain tasks with speed and efficiency, opening new possibilities to accelerate processes and digest large volumes of data, supporting humans in their work – especially where there are manual process or large volumes of data to condense.

There are different types of AI models, which can serve different functions – whether it’s to generate content, extract information or translate languages. We explore these models in our latest report, “Generative AI models – the risks and potential rewards in business” to help organizations better understand this area

Yet, as much as generative AI models may help organizations to streamline processes, for example, and free up time for employees to take on higher-value tasks, the use of generative AI has many limits and potential pitfalls. Developing and deploying AI in a responsible way is vital if organizations want to protect themselves against misuse.

“Developing and deploying AI in a responsible way is vital if organizations want to protect themselves against misuse.”

Where do you feel you make the difference in your role?

Paul Henninger: One memorable project involved helping to set up UK medical care centers at the start of the COVID-19 pandemic. These were entirely new field medical facilities intended for large number of patients in the event of a surge in infections.

KPMG in the UK supported the initiative in several areas, including helping to build a digital infrastructure for medical personnel, starting with something as simple as finding laptops for doctors and nurses. What I learned is that whether the challenge is big or small, in the end technology is there to serve human needs.

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