As organisations race to harness AI, many face challenges translating proof-of-concept projects into scalable, production-ready solutions – especially within heavily regulated environments.
Adrien Chenailler, Cloudera’s Global Director of AI Industry Solutions and Financial Services, recently shared his perspective with EITN on the shifting tides of enterprise AI adoption. He observed business leaders who have come to him, saying that they want AI because it is a top-down mandate on banks to execute AI “…without really knowing what it means and how it can impact (the business).”
He also noted that C-level execs’ performance are measured by the level of AI adoption they drive and “…how many AI features they have shipped this quarter.”
“These kinds of metrics are essentially quite negative when it comes to actual ROI.”
Adrien also opined that it is going to take a new generation of financial leaders who are fully immersed in AI, to see this ROI which may not necessarily be financial. “AI leaders have to understand that the right metric to measure AI is not dollars, yet… at least not when they are first starting.”
Rethinking workflow processes
He stressed the importance of distinguishing real, workflow-aligned innovation from mere technical demonstrations. “Most banks are doing technical POCs. They don’t think about the process behind workflows.” Adrien pointed out that ultimately these proof-of-concepts do not work because they focus on individual tasks like financial analysis, instead of reworking the entire process that goes into delivering it.
A major focus of Adrien’s message was the strategic role of private AI in compliance and regulated industries. “Private AI is needed for any kind of compliant adoption, at least that’s our view at Cloudera. That’s why we enable private AI for on-premises and in the cloud,” he explained.
The AI expert also emphasised the security and regulatory requirements facing banks, adding, “As a customer, I don’t want my banking data to go to OpenAI. That’s the last thing I want. And I think most people will tend to agree with this… (private AI) is absolutely needed for regulated industries like financial services.”
Partnerships are critical to bridging the talent and technology gap. Cloudera, Adrien noted, cultivates collaborations with specialised firms for document processing and AI observability, citing the importance of comprehensive ecosystems. “Bringing this ecosystem together allows us to have a comprehensive solution, particularly for clients that want a private AI that they can manage and control.”
What DeFi means for Cloudera
EITN also posed a question about blockchains which Adrien had interesting perspectives about.
Blockchains, or distributed ledger technology (DLT) are powering new forms of value exchange, like stablecoins and making concepts like decentralised finance (DeFi), possible.
On the role of Cloudera solutions amid this financial industry transformation, Adrien was pragmatic, “Honestly, I think we do not play in the same area as stablecoins and others. What we are is that we are able to store information and process it, but obviously, with the blockchain, you are no longer storing the information directly on a database. You are storing it on the chain.”
Many banks still locally copy transaction ledgers from blockchains for faster access and analysis. “Existing analysts in the bank do not know how to query a ledger on the blockchain right? It still has to be made accessible too,” he noted, underlining the need for versatile data platforms as DeFi infrastructures gain traction.
What we are is that we are able to store information and process it, but obviously, with the blockchain, you are no longer storing the information directly on a database. You are storing it on the chain.
Adrien Chenallier
Looking ahead, the future for AI in financial services, especially in APAC, centers on workflow automation and legacy system modernisation. As Adrien summarised, “More workflow automation, credit system modernisation, AI-infused processes in the loan origination, and loan life cycle management – streamlining the whole process is still absolutely needed, and that’s where the big change is to be.”
For business and technology leaders, the journey to AI-powered finance will demand not only tech investments but deep organisational process re-engineering. This has to go hand-in-hand with a clear-eyed assessment of where private AI can deliver the greatest impact.
