On 16 April 2018, Professor Bhimani gave a talk at the Grant Thornton’s CAM-I Meeting in London entitled “Artificial Intelligence and the Coming Transformation of Business: Is Finance leading or lagging?”
The event attracted finance, IT and marketing executives from FT 100 firms. The address discussed the evolution of internet business models and the role of accounting information in devising appropriate growth strategies.
Professor Bhimani noted the commercial potential of intelligent automation and spoke on the exponential increase in the application of AI-related systems we are witnessing across different industries. He pointed to the inevitable further acceleration of AI technology adoption in the very near term both by large global firms as well as SMEs.
The economic impact of AI is likely to power a tenth of the UK’s GNP within about ten years. In China the figure is likely to be over twice that. One factor that will certainly affect levels of commercial growth through AI platforms deployment across different countries will be national regulations around privacy, data collection and exchange and robo-ethics.
Professor Bhimani spoke also of the financial rationale for tech start-ups seeking volume growth rather than immediate profitability which underscores the long standing strategy that has been pursued by current tech giants. He told the audience that the financial basis for such a strategy will find further fuel with AI technologies.
AI, according to professor Bhimani, can only fast-pace the drive to scale and the finance function must maintain its ability to steer firms in the right direction. He stated that we will see more colossal FANG-like firms in the future but that this need not be seen as dystopian if consumers feel protected and also better served by tech-based solutions that are more and more reliant on automation intelligence.
Professor Bhimani noted that central to the UK’s pursuit of AI leadership will be its approach to balancing tech-experimentation and commercialisation with emerging regulatory safeguards – going too far in either direction will hamper its standing in the current global AI race.