Is now Good or Bad timing for investing in AI and Data

I was a panelist and the moderator for a recent webinar that gave me the opportunity to explore if “now is the time to invest in data and AI” with David Thomas, EMEA Chief Data Officer at HSBC, Alexander Denev, Head of AI - Financial Services Advisor, Deloitte, Lloyd Denzig, Chairman and Founder of ICED(AI), and with Hayley Green of Closer Still Media, who hosted the event.

The lively and insightful conversation inspired me to share some thoughts on the considerations that can help to boost business impacts and reduce organisational risks with data and AI projects.

Here are my thoughts and reflections.

It’s a turbulent time for many businesses and organisations, some of which are facing a host of challenges - including rising price sensitivity and fragile consumer confidence due to the economic implications of COVID-19. Can AI and data play a role in helping them weather the crisis? Is now the time to invest in AI and data capabilities even as other projects or strategic plans fall by the wayside?

There seems an increased awareness about what AI is, and what AI can do, what it isn’t, and what it cannot do. Yet more discussion is needed about what is real and what is hype. We need to determine what are the true benefits (the good) and real challenges (the bad). All this within the context of an ever changing regulatory landscape, particularly within the financial services sector and for public companies.

I believe we can bridge this gap by truly listening. Only by truly listening – and gaining a deep appreciation and understanding of all the points of view for the situation – can, the most appropriate intersection between increased budgetary scrutiny and essential value creation, be found.

In order to tackle this conundrum – where on the one hand it feels like now is the time to invest while, on the other hand, budgets are coming under intense scrutiny – organisations and their service partners need to work even more closely to design systems with sufficient intelligence to find the appropriate intersection between the benefits and risks of AI and data implementations. One such system is the Intelligent Interventions being enabled by some of the most innovative Data Value service providers.

By collaborating with intent, investments returns can be maximised – both in money and in effort – to enable a driving impact for the organisations. A framework for achieving such balance would be to leverage a “value predictor” - to predetermine the ROI of any AI related initiative - in order to support prioritisation and enable credible risk versus reward assessments to be undertaken.

Progressive companies are, at a minimum, investing in understanding the impacts of new data and AI methods and tools. Some are actively seeking to increase – or at least benchmark – their current capabilities. Others seem to be going even further.

In a recent example, a global retailer challenged by the combination of the age old customer returns dilemma and the current economic realities - is turning a bad situation into one that delivers good outcomes, for both itself and its customers, by enabling effective investments in AI and in data.

AI and Data Science service providers, also need to recognise that budget constraints mean that they need to enable organisations to produce more evidence that solutions will actually deliver tangible value - and in a timely manner. They also need to show patience and make time for deeper collaboration with their clients.

Data and AI have moved from those things on the long-term plan to those that now need to be considered urgent and critical - to ensure businesses can survive and thrive during these turbulent economic times.

The initiatives that give organisations the best chance of maximising ROI are those that are underpinned by frictionless collaboration - both internally and with their service partners - and those that enable better understanding of what their own needs and constraints are. Many executives today know they 'need' AI but they do not know where or how to start, and how to assess the value of a given initiative.

So, while in general, the time is indeed right to invest in AI and data capabilities, my advice would be to take these considerations into account and to address them skilfully. More than ever, we need to plan for and predict which capabilities will generate the best outcomes - now and for the future.

Thank you