Delivering Success with AI: A Talk with Finastra’s CAIO
AI has become a transformative force in the business world, revolutionising workflows, enhancing productivity, and driving innovation across industries.
As organisations grapple with the rapid advancements in AI technology, many are seeking guidance on how to effectively harness its power to deliver value both internally and externally.
The integration of AI into business operations is not without its challenges. From developing the necessary skills within the workforce to navigating the complex regulatory landscape, organisations must carefully consider their approach to AI adoption.
Moreover, the emergence of new AI leadership roles, such as Chief AI Officers (CAIOs), highlights the growing importance of strategic AI implementation in the corporate world.
But how can enterprises effectively internalise AI for value? To find out more, we spoke with Adam Lieberman, Chief AI Officer at Finastra, about the key considerations for businesses looking to leverage AI effectively.
Harnessing AI for internal value
When it comes to utilising AI for internal operations, Adam emphasises the importance of a strategic approach.
"When deployed effectively, AI can expedite and automate internal workflows and deliver incredible efficiency gains and ROI. But defining the use cases for internal teams or departments requires a similar approach to any kind of product innovation cycle", he explains.
Adam suggests that businesses must move beyond the initial excitement surrounding generative AI and focus on its strategic application within the enterprise.
This involves clearly defining use cases and equipping teams with the necessary skills to fully leverage AI-powered tools and platforms.
The process of identifying and developing AI use cases should be collaborative, bringing together leaders and technical teams.
"From this point, proofs of concept can be developed and tested with the aim of failing fast and developing 'minimal viable products', from which the use cases can be expanded".
Ensuring employees can adapt to emerging technologies is crucial for effective AI adoption. Adam points to the rapid rise of ChatGPT as an example of the immediate benefits AI can offer users.
However, the importance of establishing a roadmap to achieve 'enterprise fluency' in AI technologies is crucial.
"It's also important to devise pathways that take into account the technical aptitude of individual employees, teams and departments, as implementations are rarely a 'one-size-fits-all' affair", Adam notes.
This tailored approach ensures that employees across different departments can effectively integrate AI into their workflows.
Approaching AI-led innovation
When it comes to developing customer-facing AI solutions, Adam advises a comprehensive assessment of an organisation's AI-readiness. This includes evaluating existing architecture, infrastructure, and available data.
"Those taking a lead on AI strategy must have a fundamental understanding of what is required to build teams around a problem and develop solutions that meet the standards required—and not only from a legal and regulatory perspective", he states.
The importance of addressing ethical considerations, such as eliminating bias and ensuring model explainability, cannot be overstated.
With the increasing global focus on AI regulation, organisations must remain agile and prepared for changes in the legal landscape.
By closely tracking the evolution of AI laws and regulations, understanding how comparable entities are developing compliance practices, and considering the potential impact on product and technology adoption roadmaps, enterprises can adapt..
"When legal or regulatory developments indicate that AI solutions or data handling practices may need to be reevaluated, it's the job of technology leaders, such as CAIOs, to make sure the business is aware of the potential impact on the business", Adam explains.
The role of AI leadership
The emergence of roles like Chief AI Officers reflects the growing importance of strategic AI implementation in organisations.
Adam, who holds this position at Finastra, describes his role as focusing on "the strategic enablement of artificial intelligence across the business".
This encompasses a wide range of responsibilities, from assessing infrastructure to developing governance policies and reviewing AI use cases.
"It's a broad role focused on the end-to-end usage of artificial intelligence with respect to the business and industry", Adam concludes.
As AI continues to reshape the business landscape, organisations that can effectively integrate this technology into their operations, while navigating the associated challenges, will be well-positioned to thrive in an increasingly AI-driven world.
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