Banks Lagging in Adopting Generative AI,  Report Finds


  • Banks lag in gen AI roadmap establishment.
  • Customer dissatisfaction persists with chatbot resolutions.
  • Bank employees welcome gen AI copilots eagerly.

Despite the widespread recognition of the transformative potential of artificial intelligence (AI) in the banking sector, a recent report by Capgemini reveals that less than one in ten retail banks have established a viable roadmap for the implementation of generative AI (gen AI) capabilities at scale. 

The study, which evaluated 250 retail banks globally, highlights a concerning lack of readiness among financial institutions to embrace and effectively implement intelligent transformation.

Banks confront funding challenges and regional disparities in AI adoption

A significant barrier to the adoption of advanced AI technologies like generative AI is the lack of adequate funding. With expansion becoming increasingly difficult amidst an uncertain economy, many banks are focusing on inward growth strategies. 

Chief experience officers (CXOs) are planning to boost investment in digital technology by up to 10%, aiming to enhance services and operations. However, the inability to scale new technologies efficiently poses a significant challenge for many banks.

The report reveals significant regional disparities in readiness for intelligent transformation. While North America exhibits a 27% low readiness rate, Europe follows closely with 31%. However, the Asia-Pacific (APAC) region lags significantly behind, with 48% of banks scoring low in readiness. 

This indicates a pressing need for banks worldwide to act swiftly to avoid what the report terms as ‘generative AI silent failure.’

Measurable success crucial for sustainable growth

To navigate ongoing challenges effectively, banks must focus on intelligent solutions embedded with AI-driven capabilities. However, the report underscores the importance of establishing measurable success metrics. Alarmingly, only 6% of banks surveyed have set key performance indicators (KPIs) to measure AI impact and continuous monitoring.

The delayed realization of suboptimal results from AI experiments poses a significant risk, as evidenced by the dissatisfaction expressed by 39% of executives with AI use case outcomes.

Generative AI holds immense potential to enhance efficiency and customer experience across the retail banking value chain. Bank employees, particularly those focused on operational activities and customer onboarding, welcome the potential of generative AI copilots to automate tasks such as fraud detection, data visualization, and personalized content creation. 

The report suggests that banks could optimize up to 66% of time spent on operations through AI-powered intelligent transformation.

Conversational AI to address customer dissatisfaction

Despite the shift towards digital customer service channels, dissatisfaction persists among bank customers, particularly regarding chatbot interactions. The report highlights the limitations of traditional rule-based chatbots and emphasizes the need for conversational AI capabilities to address complex queries effectively. 

By implementing intelligent contact centers equipped with advanced AI-driven systems, banks can alleviate customer dissatisfaction and reduce call abandonment rates.

the Capgemini report underscores the urgent need for retail banks to accelerate their adoption of generative AI and other advanced technologies to remain competitive in an increasingly digital landscape. 

Establishing robust roadmaps, setting measurable KPIs, and investing in employee training are essential steps towards achieving sustainable growth and enhancing customer experiences. As the banking sector continues to evolve, embracing AI-driven solutions will be paramount in navigating the challenges and opportunities that lie ahead.

Disclaimer. The information provided is not trading advice. Cryptopolitan.com holds no liability for any investments made based on the information provided on this page. We strongly recommend independent research and/or consultation with a qualified professional before making any investment decisions.

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Emman Omwanda

Emmanuel Omwanda is a blockchain reporter who dives deep into industry news, on-chain analysis, non-fungible tokens (NFTs), Artificial Intelligence (AI), and more. His expertise lies in cryptocurrency markets, spanning both fundamental and technical analysis.

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