Unlocking the value of AI with data

By Theodora Lau and Bradley Leimer of Unconventional Ventures

Business needs are changing, and companies must adapt. According to Global AI Adoption Index 2021 — a new research commissioned by IBM in partnership with Morning Consult — 74% of companies are exploring or deploying artificial intelligence (AI), with adoption being driven by changing business conditions and COVID-19. 

However, the journey to digital transformation is never easy. While AI may be changing the way businesses operate in fundamental ways, and advances in technology have made AI more accessible, the lack of AI skills, increasing data complexity, and data silos are some of the top barriers to broader AI adoption.

With challenges come opportunities: Investment in digital transformation is expected to reach $7.4 trillion by 2023, according to IDC. Digital transformation is no longer a competitive advantage, but an existential priority for nearly all industries and applications. 

How then can businesses unlock the value of data and innovate to meet the demands of the future? 

“There is no AI without IA” (Infrastructure Architecture)  

?~ Rob Thomas, SVP, IBM Cloud and Data Platform

And we are just getting started.

Data is everywhere

According to IDC, by 2025, worldwide data volume will grow to 175 zettabytes, with as much of the data residing in the cloud as in data centers. Imagine a tall stack of BlueRay discs that can get you to the moon and back 23 times. 

But having data is only one piece of the puzzle. To be able to fully leverage data as the fuel for digital transformation activities, we need a trifecta of people, process, and technology. 

A recent study by Gartner showed that more CEOs than ever are citing digital change and investment as a priority, with AI being the most industry-impactful technology that leaders across different industries and organizations plan to focus on. However, that same study also revealed that “a majority of CEOs polled did not yet have designated data officers such as chief digital officers or chief data officers”. 

With disparate data sources hidden in so many independent silos, the ability to collate and process data in a real-time manner to create actionable insights and results is one of the top priorities of businesses in this digital era. Without the right leadership to steer these crucial activities is akin to driving without navigation assistance — making an already challenging task even more difficult. 

Imagine AI as a superhighway that connects different communities with different on- and off-ramps, where each community represents different data sources. How will we design the highway and best determine which communities will be connected? How will the infrastructure scale as the ecosystem grows and who will have access to it? Who will be the architects, designers, and planners for the project? And what are our guiding principles to ensure trust, equity, and fairness?

Creating an AI-powered organization requires more than simply technology change. Just as numbers are meaningless without context, data alone is not useful without the right environment and execution, both operationally and organizationally. 

Accelerating digital transformation and putting AI into action will require us to overcome the challenges of talent, data complexity and trust. 

1. Talent: Many organizations struggle to find the right talent to fulfill their AI objectives. From research to applications, and from building to scaling trusted AI, having diverse cross-functional teams with the right expertise and knowledge is crucial to our ability to understand our AI data needs, and to work with trusted partners as we build and extend the ecosystem. 
2. Data governance and strategy: The growing abundance of data presents an opportunity for the financial services industry and beyond, to fast track innovation and deliver hyper-personalized customer experiences. Beyond having well-curated training data and the right tools and platforms to insert trusted AI models, we must ensure we have a data strategy in place to identify and prioritize use cases to deploy, and a plan to tackle increasing data complexity and cybersecurity challenges.
3. Culture and trustworthy AI: While trust is a major currency in financial services, it is not one to be taken for granted. Building trust in processes and models requires transparent, robust and explicable AI underpinned by trusted data across open ecosystems. As we introduce emerging technologies in the process, we must ensure the output is fair and reliable, while minimizing monetary, regulatory and reputational risk. Fostering a culture committed to ethical and responsible use of technology is one of the key pillars to building an inclusive future for AI in financial services. 

Turning possibilities into realities

The opportunity is in front of us not only to think strategically about AI, but to adopt it to unlock the potential of data and deliver added customer lifetime value. Having a trustworthy, ethical, and explainable AI not only helps to maintain brand integrity and secure customer trust, it is also crucial for regulatory compliance.  

We are still very early in our AI journey. As our work and life habits continue to evolve, our operations will need to run anywhere and everywhere. How will we reimagine a superior customer-centric experience for the post-pandemic lifestyle? How can we rethink risk assessment and financial planning to adapt to changing demographics? How should we redesign employee experience for the hybrid workforce of the future? How do we best minimize unintended bias or mitigate inherent bias? 

These are all important questions to consider.

Businesses that can build trust in their data and data mode through governance, accuracy, and explainability will be able to capitalize on these new opportunities and infuse AI-powered capabilities in the data anywhere future, turning possibilities into realities. 

In our next blog, we will examine some specific use cases and companies who are leading the way in integrating AI as part of their digital transformation.

So what’s next on your AI journey? 

Register here for the Data and AI Virtual Forum for FSS on May 27 and discover how banking, financial markets, and insurance institutions use trusted AI to speed digital transformation.