It seems that AI is on everyone’s mind these days but, in some ways, figuring out how to get your organization ready to use it raises more questions than it answers.

For example, on a recent Avanade North America webinar on AI Readiness in Banking someone asked me whether the responsible use of AI should be mandated on banks by regulators, or should financial institutions lead the regulatory agencies? It’s a provocative topic, and one that I’ll address in another blog. But to be sure, how the regulators respond to AI is out of our control.

Rather than try to predict where they’ll land with regulations, my view is that banks should focus on what they can control. For instance, to really thrive in an AI-first ecosystem, banks must get their organizations ready. Indeed, according to Avanade’s new research on AI readiness, 92% of executives surveyed believe that their organizations must shift to an AI-first operating model within the next 12 months to stay competitive and meet customer expectations. Here are five essential areas banks can and must address:

1. Define your responsible AI principles. Only 4 in 10 banking executives report having a complete set of guidelines. And yet, this is a critical component of understanding and managing risk tolerance, being compliant, and most importantly, building confidence and trust in AI technologies. Organizations must define their responsible AI principles and policies anchored in their AI mission.

2. Get your proprietary data ready. 56% of research respondents believe that low external ecosystem maturity restricts their ability to accelerate AI initiatives. That’s because at many financial institutions, a confusing web of overlapping technology and tools by cloud providers, analytics vendors and other niche players exists across business units. These silos and redundancies have led to data not being collected for use in an advanced and meaningful way. Banks must take a strategic and disciplined approach to acquiring, refining, safeguarding and deploying data.

3. Start experimenting and measure your success. Getting your data ready doesn’t preclude you from experimenting. Our research shows that banking CXOs are most excited about use cases that address customer onboarding; automation of risk, regulation and compliance requests; and monitoring fraud detection and auto-healing of security loopholes. Now is a great time to launch small-scale pilots in a compliant environment to create a value framework, understand potential impact and evaluate the business case for scaling.

4. Refresh your talent and location strategy. 64% of research respondents across industries don’t believe that AI will reduce the number of human roles. Instead, they anticipate that headcount will increase by 9% by the end of 2024. AI will disrupt the workplace, and as leaders, we need to make sure that HR and training within organizations are involved early to understand new roles, new ways of working and the impacts on talent strategy and sourcing. They will also be invaluable partners in critical AI literacy efforts to ensure that people are ready at the right time to use the technology in the most effective way.

5. Select your ecosystem partnerships for scale. A strong partner will guide you on the assessment and implementation of data and technology tools to enable use cases. For those organizations struggling to operationalize proofs of concept due to a lack of knowledgeable talent, the right partner will have the expertise to execute and scale. They can even help establish a center of enablement with a core team bringing the right skill set to enable technical capabilities.

If you address these five essentials, your banking organization will be well on its way to AI readiness in this new competitive landscape.

If you’d like more on the topic or missed the webinar, here are some resources to explore:
• Read through the recently released Avanade AI Readiness Report
• Access my presentation
• Sign up for an AI organizational readiness workshop