Riverbed Survey.. While Financial Services Are Ahead of the AI Curve, Data Concerns and Gaps Are Impacting AI’s Full Potential

The Riverbed Global AI & Digital Experience Survey provides unique insight into the Financial Services sector – including its approach, attitude and adoption strategies for successfully implementing AI now and into the future.

Dubai, United Arab Emirates – October 28, 2024

Riverbed, the leader in AI Observability, announced the Financial Services results of the Riverbed Global AI & Digital Experience Survey. The survey found that organizations in the financial sector are mostly forward-thinking with their attitudes towards AI technology, and 94% of business and IT decision makers agree that AI will help them deliver a better digital experience for their end users.

Compared to other sectors, Financial Services is also one of the most prepared for AI adoption. Currently, 46% of leaders surveyed in the Financial Services sector say their organization is fully prepared to implement their AI strategy now (against a 37% average). However, with the majority not fully prepared, a readiness gap still exists within the Financial Services industry. Additionally, Riverbed’s research reveals that Financial Services leaders require reassurances in data confidentiality and accuracy before they can deliver secure digital experiences for their end users.

At the same time, Financial Services decision-makers are also more assured in the practical benefits of AI than most, with 96% of respondents believing it provides their business a competitive advantage. Financial organizations are vying for an edge against digital-native startups – which demands a strategic and practical approach to AI that reduces costs, increases efficiency, offers bespoke services, and mitigates customer risk.

While AI is still maturing, it’s evident that trust in AI is growing with 65% of Financial Services IT and business leaders agreeing they would rather automate a major IT upgrade than sit in the back seat of a driverless car in a city – which is 4% more than the global average.

Investment in Infrastructure and Talent May Help to Offset Generational Concerns

Nearly all leaders in the Financial Services industry (99%) consider AI to be either a key strategic priority or at least moderately important across their organization. Furthermore, the perception of AI within Financial Services organizations is slightly more enthusiastic than in other sectors, with 62% of leaders believing their teams are positive towards the adoption of the new technology, and only 3% skeptical (versus 59% and 4% respectively as the global average).

Financial Organizations Set to Improve DEX and Operational Efficiency With AI

In last year’s Riverbed Global Digital Employee Experience (DEX) Survey, 92% of Financial Services business and IT leaders believed pressure on IT resources would increase in response to the need to provide a greater DEX for employees and customers. Now, it’s becoming clear that AI automation can offer a solution for these heightened expectations, with nearly half (49%) of financial leaders reporting that AI implementation has either optimized resource utilization or will begin to do so within three years – benefitting workplace morale by supporting stretched teams with their daily tasks.

Over the same time frame, leaders in the Financial Services sector expect AI to streamline their operations by improving workflow automation (71%), automated remediation (62%) and autonomously offering 24/7 support via tools like chatbots (62%).

Currently, the primary reason for using AI in the Finance Sector is almost equal between driving operational efficiencies (51%) versus driving growth (49%) – demonstrating that these Financial Services organizations are currently more advanced in terms of AI maturity than other industries. However, it’s expected in three years’ time that the primary focus will shift towards driving growth (54%), with operational efficiencies becoming slightly less (46%) of a priority.

Generative AI is also expected to gain traction in IT operations over the next 12-18 months. According to the results, currently 36% of Financial Services organizations have put Gen AI use cases for IT operations in production or have completed prototypes they now plan on taking to production. Leaders in the industry expect to become even more progressive as the sector revolutionizes further, with use cases materializing into 71% implementation over the upcoming 12-18 months. All other respondents remain in the ideation phases for their potential AI usage.

Despite Being Ahead of Other Industries, There Are Still Doubts Regarding AI Data Integrity and Readiness

The survey revealed three key areas in which there’s a noticeable gap between AI enthusiasm and implementation, although Financial Services continue to display above average progress in preparedness. As referenced earlier, there is a Readiness Gap with less than half (46%) claiming they are fully prepared to implement AI projects today, though this is nearly 10% higher than cross-industry averages.

There’s also a Reality Gap, with 85% of leaders in the industry saying they’re either ‘significantly’ or ‘slightly’ ahead of their competitors with their adoption of AI for IT services and digital experiences. This gap between perception and reality indicates many leaders are overconfident about where their IT function is on their AI journey relative to their industry peers.

However, the biggest concern for the Financial Services industry is the Data Gap, which represents the area in which financial organizations must seek improvements to compete with the cross-sector average – although this is still a shared concern across all industries.

“As the financial sector traditionally handles more sensitive customer information than other industries, it’s not surprising that 80% of leaders are worried about their proprietary data being accessible in the public domain due to AI usage,” said Jim Gargan, Chief Marketing Officer, at Riverbed. “What’s more, leaders also have reservations regarding the effectiveness of the data at their disposal, with only about a third rating their data as excellent for completeness (36%) and accuracy (34%) – the lowest across all industries.”

Gargan continued, “Great AI starts with great data and the data gap is one of the biggest inhibitors to AI success. At Riverbed, we are helping our customers address this data gap with a practical approach to AI, which includes an AI-powered platform that provides full-fidelity data and observability across the entire IT landscape. Additionally, Riverbed’s AI is safe, secure and accurate, providing real value with data-driven insights that allows organizations to deliver optimized digital experiences and improved business outcomes.”

Observability and Authentic Data Anticipated to be Crucial for Full AI Implementation

The survey’s findings indicate that financial services organizations are even more keen to address the data gap than their counterparts in other sectors. Most leaders (92%) say that using real data, rather than synthetic data, is crucial in AI efforts to improve DEX, and 91% agree that observability across all elements of IT is important in an AIOps strategy. This is several percentage points higher than other industry sectors.

Leaders in the Financial Services industry are more aligned with the broader consensus on the benefits of other AI strategies, including:

At least 84% say observability is either extremely or moderately important when overcoming network blind spots, including public cloud, remote work environments, Zero Trust architectures, and enterprise mobile services. 

45% have established observability and/or user experience teams; and over half of organizations (55%) have formed dedicated teams to address AI preparedness.

Financial Services organizations are clearly adjusting their infrastructure as they look to continue optimizing the benefits of emerging technologies. AI is undeniably a core aspect of the industry’s future – but strategic adjustments and increased data security are still necessary before full integration can be achieved. The financial services organizations that act swiftly to address these gaps will not only produce secure and seamless operational performance, but also gain a significant competitive advantage within this increasingly AI-driven landscape.