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7 Savoy Court, London, WC2R 0EX
Email: contact@relata.ai
Charlie Henderson
Quick reads
“You should know your problem first and realise AI can be a solution. If you don’t understand what you are trying to solve, you are carrying a hammer looking for a nail and AI is going to be of no real use to you.”
The last two years has seen a dramatic acceleration of AI adoption across the financial services sector. An empirical survey jointly conducted by the Cambridge Centre for Alternative Finance (CCAF) and the World Economic Forum (WEF) in Q2-Q3 2019 found that 85% of surveyed companies are utilising some form of AI across business operations. Moreover, Artificial Intelligence is expected to turn into an essential business driver across the Financial Services industry in the short run, with 77% of all respondents anticipating AI to possess high or very high overall importance to their businesses within two years.
As well as an acceleration in the adoption of AI technologies, we are also seeing a shift in its use, from being focussed on risk and cost management, towards driving increased revenue generation. This shift is resulting in increased demand for our Synapse product as enterprises seek real-time insights into how to improve front-office performance and increase the ROI of their sales teams. In addition, the CCAF and WEF white paper, Transforming Paradigms: A Global AI in Financial Services Survey, found that 95% of surveyed firms expect to be harnessing AI capabilities in the generation of new revenue potential within two years.
According to Microsoft UK CEO, Cindy Rose, “there is now a clear link between an organisation’s full deployment of AI technologies and its ability to accelerate growth, improve productivity and retain a competitive edge.” Organisations already moving from experimentation to implementation are performing significantly better on productivity and business outcomes than those still caught in the early stages of exploration. As Mitra Azizirad, Corporate Vice President for Microsoft AI, explains: “In the next five years, every successful company will become an AI-company. It is now the next level of competitive differentiation.”
Regardless of industry, sector or vertical, the successful implementation of a digital transformation strategy lies primarily with its alignment to business goals. We have moved away from implementing AI on a technology-based initiative level, towards building it in to the wider enterprise strategy. In Boston Consulting Group and MIT Sloane Management Review’s white paper Winning with AI, CIO of Roche Pharmaceuticals, Steve Guise, lays out the argument that organisations need to keep the focus on strategy, and executives need to appreciate the ways in which “AI can influence entire business models”.
As Nick Wise, CEO of OceanMind, puts it: “You should know your problem first and realise AI can be a solution. If you don’t understand what you are trying to solve, you are carrying a hammer looking for a nail and AI is going to be of no real use to you.”
As previously mentioned in FeedStock’s article on the importance of enterprise-wide data-literacy, the more data-driven an enterprise is in its business operations, the more reliant it becomes on its data sources. We are continually speaking to C-Suite executives seeking to leverage automated data-capture technology across myriad streams such as Bloomberg and FactSet terminals and legacy email and browser technologies. It’s hardly surprising therefore that research done on 151 organisations across 33 countries found that leveraging alternative datasets to generate novel insights is a key part of harnessing the benefits of AI with 60% of all respondents utilising new or alternative forms of data in AI applications.
According to figures from TechJury, the global AI market is expected to be worth almost $60 billion by 2025, an increase of $58.6 billion from 2016. Closer to home, the UK government has shown its intention to promote and rapidly progress the AI industry in the form of a £115 million investment in AI training at graduate level. The market is awash with statistics which demonstrate the widening of the gap between ‘AI Leaders’ who are reaping the benefits of improved revenue-generating capabilities versus ‘AI Laggards’ who tend to remain stuck in the experimentation phase and fall into what Microsoft refers to as the “Adoption Chasm”. Indeed, the previously referenced Microsoft white paper revealed that organisations already making progress on their journey to implementing AI at scale are performing 11.5% better than those who are not, a figure that has more than doubled since 2018. In particular, AI Leaders are more productive (11%), show higher profitability (12%) and experience better business outcomes (11%). This is an extraordinary increase and clear evidence of the significant benefits awaiting companies who act now to embed AI across their business.
