Generative AI will transform almost every aspect of business operations in the coming years. From data analysis and marketing to optimising operational efficiency and enterprise value (EV), no area will be unaffected.
In our previous articles in this series, we looked at the technologies behind generative AI and explored its impact on business strategy in the context of three strategic frameworks: Porter’s Five Forces, the VRIO framework, and KPMG’s own Nine Levers of Value. In this article, we recap the core competencies of generative AI, explore the reason firm’s engage consultants, and how generative AI might change the consulting profession.
Core competencies of generative AI
When deployed at scale, generative AI can improve efficiency and creativity across a broad spectrum of business activities. While in the long term, generative AI could replace many roles currently performed by humans, for the time being it’s more likely to be a complimentary tool that will support existing teams, helping to perform tasks quicker and more accurately.
In terms of business performance, AI technology has implications for market leading firms as well as those wishing to improve their market share. Because generative AI is trained on proprietary data, market leaders have the potential to extend their advantage lead if they implement generative AI to support the most value-add/differentiating areas of their business. Conversely, if firms with smaller market share can implement the technology faster and more effectively, they could gain competitive advantage through faster time to market, increased margin, or more responsive customer service. Not to mention the margin-improving potential of quickly automating repetitive, low-level tasks across any organisation, or the new insights that could be derived from using generative AI to spot patterns across data sets.
Why do firms engage professional services?
In a 1982 Harvard Business Review article, Professor Arthur Turner described a hierarchy of consulting purposes (see Figure 1 below) which are applicable for the wider professional services sector. Despite the 40 years since publication, these purposes hold true today, although specific deliverables are likely to have changed.
Figure 1 – A Hierarchy of Consulting Purposes Source: A. Turner (1982) Consulting is More Than Giving Advice. Harvard Business Review. 60 (5), p. 120
It is clear that some of the purposes of modern professional services detailed in Figure 1 could already be delivered by generative AI, such as providing information, conducting diagnoses, and providing recommendations. However, by combining the process and analytical power of generative AI technologies with the experience and know-how of professional service firms, generative AI could act as a force-multiplier, with additional value being delivered at previously impossible timescales.
How can advisors derive value from generative AI?
As explored in our previous articles, asking the right questions is crucial to getting the best output from generative AI. If Henry Ford had asked ChatGPT his infamous question of what his customers wanted ChatGPT’s likely answer would have been ‘faster horses’. If he had instead asked ChatGPT to imagine a future beyond horses, using the latest technology applied to personal transport solutions, the answer would likely have been totally different.