How Can AI Be a Catalyst to Value?

The nature of value, and how we view it and quantify it, is changing.

As Jean-Paul Mazoyer, Deputy General Manager at the international French bank Credit Agricole, told me, “We need to detangle value from short-term profit.” And that’s coming from a banker.

The days of stakeholders prioritising short-term profit alone as an objective are gone. The era of the 1980s, full of “greed is good” mantras displayed by movies like Wall Street, is outdated and doesn’t fit with the more socially conscious and environmentally-driven world that is arising. Instead, the seeds are being sown for creative disruption, with a focus on decarbonisation, growing environmental citizenship, and mitigating a looming food and energy crisis. It all begs the question, how can we re-engineer capitalism in the 21st century?

Business is adapting to these trends. A new class of VC firms, such as 2050, is emerging. They endorse long-term returns and propositions that put people, society, and the planet first. This evolution is seeing entrepreneurs fund an educational revolution to explore digitalisation and impact, new business classifications such as B Corp redefining the concept of corporate value, and many startups, such as Provenance (tracks production origin) and Impossible Foods (meat alternative), reinventing daily impact and profit.

Despite all this, when it comes to AI, most companies associate its implementation with short-term operational gains (speed, agility, stack efficiency) over impactful transformations. We have to reposition the definition of value and capture the role AI can play.

So, what should businesses consider as value to build resilience?

Looking ‘Beyond Profit’: Adaptive Value

Many companies are on the journey of progressing from descriptive to predictive analytics and have already implemented a few algorithms. It’s a good start, but why work with probabilities? Companies need decisions, not anticipation: effective decision-making — connected, contextual, and continuous — results in adaptive value, including greater transparency, risk management, an upskilled workforce, and scalability.

In order to make these decisions, you have to imagine various futures and tailor processes and mindsets to adapt faster to changing contexts.

Transformational or Purpose Value

There’s no point in achieving efficiency for efficiency’s sake. When adopting AI, the goal is to reach transformational value that helps a business deliver its mission, whatever that may be.

It’s perhaps helpful then to frame this transition as purpose value rather than transformational value. By adopting this framing, we can remove the tension that tugs between small yet mighty changes, between a business that acts for the good of society and one that serves the wealth of a few.

Purpose value keeps us on our toes because metrics will evolve. It keeps us motivated because it unifies strength and reputation (as long as your mission is not to suffocate people with nicotine, melt the ice cap, or inundate kids with sugar-fat-full-sweets). Gartner predicts that by 2026, “organisations that develop trustworthy, purpose-driven AI will see over 75% of AI innovations succeed, compared to 40% among those that don’t.”

We have to harness both adaptive and purpose value in relation to operational efficiencies. The way to achieve this is to empower staff with accessible data and give them time to explore and collaborate, helping to shift mindsets from short-term profit towards long-term value. To wholly realise a reality ‘beyond profit,’ companies need to formulate a repeatable and scalable methodology that channels collective intelligence.

Extraordinary People Through Collective Intelligence

While there is much doom-mongering in the news about AI’s development, its role isn’t about taking over humans. Rather, it’s about enhancing our collective intelligence and, in short, making us less ordinary. Through this, we are freed from the constraints of bland, repetitive tasks and instead provided with the time and freedom to build an easily shareable collective memory that can add to each other’s strengths.

As the saying goes, ‘there is strength in numbers.’ In the workplace, there is intelligence in numbers, and AI and hyperconnectivity are about to deliver widespread implementation of collective intelligence. Our capability to solve issues will be accelerated through a combined approach of connecting people on a massive scale towards meaningful goals with the additional strength of anticipative analytics (e.g. ML). It’s collaborating with, rather than battling, machines.

This power can also be used to enhance staff well-being and happiness. Data can simulate real-life experiences and allows us to move beyond just retention goals, understanding the value of well-being and self-realisation for creating collaborative and creative environments. At the heart of this, development must come from a responsibly-driven approach.

The detangling of value from short-term profit can transpire from AI enhancing collective intelligence by integrating adaptive and purpose-driven value. As a business’s values evolve, so too does its data — the two assist each other. This paves the way for an economy where, as described by Jacqueline Novogratz (Founder and CEO of Acumen), “we use the tools of capitalism without being controlled by them.”

About the Author

Stephanie Griffiths is Field – CDO at Dataiku. Stephanie is an experienced keynote speaker at digital, innovation, and fintech conferences, with expertise in change management, human-centered design, and the everyday application of AI. As a Field – Chief Data Officer at Dataiku, she is focused on driving business value and digital transformation through the application of AI. She has just been awarded a Research Fellowship at the Open Data Institute in London, focusing on AI & Business Value.

Stephanie is also an ambassador for the Dataiku Women in Data Science (WiDS) conference, an event dedicated to inspiring and educating data professionals and supporting women in the field. The 2023 event will be held in Madrid on the 11th of May.

Prior to her role at Dataiku, Stephanie was CMO for Ffyn, a fintech in Asset Management, created a prototyping studio, and held various Sales & Strategic positions within WPP agencies in Telecommunications and Finance.

Her entrepreneurial experiences led her to be a business mentor for APX  in Berlin, a JV between Axel Springer and Porsche focused on early-stage investment in innovative startups. She was a Board Member at the French Tech Berlin, for Visit Britain, and an international trade advisor for the French Government in Berlin.

Her passion for education and tech, led her to be a visiting lecturer at ESADE, and ISEG and coach kids at AppsforGood. Fluent in English, French, and Spanish, Stephanie is an accomplished and engaging speaker.

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