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Financial Services Industry Is Ready to Lead on AI Adoption, Once Data Concerns Are Addressed

Mike Marks
Riverbed

The financial services industry (FSI) is poised to take the next steps in using AI as a tool to drive business growth, improve operations and deliver a better digital experience for users. However, before taking full advantage of AI's capabilities, leaders first must address several readiness issues as well as concerns over data confidentiality and accuracy.

Leaders in the financial services sector are bullish on AI, with 95% of business and IT decision makers saying that AI is a top C-Suite priority, and 96% of respondents believing it provides their business a competitive advantage, according to Riverbed's Global AI and Digital Experience Survey. Financial services organizations, looking to fend off digital native startups, are pursuing a strategic approach to AI that can reduce costs, increase efficiency, mitigate customer risk and enable customized services.

The industry is also more confident than most sectors in its ability to follow through on widespread AI adoption, with 46% of leaders saying they are fully prepared now to implement their AI strategies, compared with a 37% average across all sectors surveyed. While confidence is high, a majority within the industry are not currently prepared for AI according to the data, revealing a readiness gap in adopting AI, one of three key areas leaders need to address in the year ahead. Leaders in FSI, like those in other sectors, also have a reality gap, with 85% saying they're either "significantly" or "slightly" ahead of their competitors, indicating a level of overconfidence in their own progress. The biggest challenge facing the industry is the data gap, with leaders expressing concerns about both the security of their data and its usability.

Image
Riverbed 2024-11-2

Financial services handle more sensitive customer information than other sectors, and 80% of leaders are worried about the security implications of their data being accessible via the public domain, with their primary concerns being data privacy, regulatory compliance and cybersecurity threats. Despite high confidence in AI's abilities, decision-makers have less faith than those in other sectors in the quality of their data, with only about a third rating their data as excellent for completeness (36%) and accuracy (34%). They need reassurance in data confidentiality and accuracy before they can deliver secure digital experiences for their users, recognizing the need for full-fidelity data.

Younger Employees Are on Board with the Transition

Those concerns notwithstanding, FSI leaders are optimistic about a transformative shift toward AI, with 89% expecting to be fully prepared to implement their AI strategy by 2027 (up from the 46% who say they are ready now). That growth is reflected in their use of generative AI, with 36% saying they have currently implemented or prototyped generative AI, and 71% saying they will in 12 to 18 months.

Leaders say their workforces are mostly enthusiastic about AI, with 62% saying their teams have favorable views (compared with a 59% global average), while only 3% view AI skeptically (compared with 4% globally.) Within their workforces, leaders say Generation Z employees are the most comfortable with AI, at 55%, followed by millennials, at 36%, well ahead of Generation X and baby boomers, at a combined 9%. This suggests AI could eventually replace knowledge-holders; a generational shift in attitudes towards the technology could be why 68% of organizations are increasing investments in infrastructure and talent.

Image
Riverbed 2024-11-1

What Financial Service Leaders Expect from Automated AI

Younger generations of workers are also the most insistent about having a positive digital experience, which leaders believe can be improved via AI automation. Last year's survey found that 92% of business and IT leaders in financial services said the need to provide improved DEX for employees and customers would increase pressure on IT resources. However, nearly half (49%) of financial leaders reported that AI implementations have already optimized resource utilization or will do so within three years, and 94% agreed that AI would help deliver a better digital experience for users. By supporting stretched IT teams, AI implementations can help boost morale.

Other key areas that leaders expect AI will improve includes workflow automation (71%), automated remediation (62%) and autonomously offering 24/7 support via tools like chatbots (62%).

Image
Riverbed-2024-11-3

As IT decision makers increasingly move into C-Suites — 78% said they have a seat at the table — suggesting IT's critical role in driving business innovation is gaining traction. For example, these leaders say technologies such as AI and unified observability are critical to providing exemplary DEX, with 95% saying that unified observability is important (55% said critically important), and 94% calling for greater investment in unified observability solutions.

The next three years will also see a shift toward using AI to drive growth. Currently, leaders say their primary reasons for adopting AI are split almost evenly between operational efficiencies (51%) and driving growth (49%), but 54% expect fueling business growth to be the focus by 2027, ahead of operations, at 46%.

Finally, the survey found that properly implementing AI tools will be essential to boosting productivity, retaining staff, enabling collaboration and staying competitive in the FSI environment.

Mike Marks is VP of Product Marketing at Riverbed

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Traditional observability requires users to leap across different platforms or tools for metrics, logs, or traces and related issues manually, which is very time-consuming, so as to reasonably ascertain the root cause. Observability 2.0 fixes this by unifying all telemetry data, logs, metrics, and traces into a single, context-rich pipeline that flows into one smart platform. But this is far from just having a bunch of additional data; this data is actionable, predictive, and tied to revenue realization ...

Financial Services Industry Is Ready to Lead on AI Adoption, Once Data Concerns Are Addressed

Mike Marks
Riverbed

The financial services industry (FSI) is poised to take the next steps in using AI as a tool to drive business growth, improve operations and deliver a better digital experience for users. However, before taking full advantage of AI's capabilities, leaders first must address several readiness issues as well as concerns over data confidentiality and accuracy.

Leaders in the financial services sector are bullish on AI, with 95% of business and IT decision makers saying that AI is a top C-Suite priority, and 96% of respondents believing it provides their business a competitive advantage, according to Riverbed's Global AI and Digital Experience Survey. Financial services organizations, looking to fend off digital native startups, are pursuing a strategic approach to AI that can reduce costs, increase efficiency, mitigate customer risk and enable customized services.

The industry is also more confident than most sectors in its ability to follow through on widespread AI adoption, with 46% of leaders saying they are fully prepared now to implement their AI strategies, compared with a 37% average across all sectors surveyed. While confidence is high, a majority within the industry are not currently prepared for AI according to the data, revealing a readiness gap in adopting AI, one of three key areas leaders need to address in the year ahead. Leaders in FSI, like those in other sectors, also have a reality gap, with 85% saying they're either "significantly" or "slightly" ahead of their competitors, indicating a level of overconfidence in their own progress. The biggest challenge facing the industry is the data gap, with leaders expressing concerns about both the security of their data and its usability.

Image
Riverbed 2024-11-2

Financial services handle more sensitive customer information than other sectors, and 80% of leaders are worried about the security implications of their data being accessible via the public domain, with their primary concerns being data privacy, regulatory compliance and cybersecurity threats. Despite high confidence in AI's abilities, decision-makers have less faith than those in other sectors in the quality of their data, with only about a third rating their data as excellent for completeness (36%) and accuracy (34%). They need reassurance in data confidentiality and accuracy before they can deliver secure digital experiences for their users, recognizing the need for full-fidelity data.

Younger Employees Are on Board with the Transition

Those concerns notwithstanding, FSI leaders are optimistic about a transformative shift toward AI, with 89% expecting to be fully prepared to implement their AI strategy by 2027 (up from the 46% who say they are ready now). That growth is reflected in their use of generative AI, with 36% saying they have currently implemented or prototyped generative AI, and 71% saying they will in 12 to 18 months.

Leaders say their workforces are mostly enthusiastic about AI, with 62% saying their teams have favorable views (compared with a 59% global average), while only 3% view AI skeptically (compared with 4% globally.) Within their workforces, leaders say Generation Z employees are the most comfortable with AI, at 55%, followed by millennials, at 36%, well ahead of Generation X and baby boomers, at a combined 9%. This suggests AI could eventually replace knowledge-holders; a generational shift in attitudes towards the technology could be why 68% of organizations are increasing investments in infrastructure and talent.

Image
Riverbed 2024-11-1

What Financial Service Leaders Expect from Automated AI

Younger generations of workers are also the most insistent about having a positive digital experience, which leaders believe can be improved via AI automation. Last year's survey found that 92% of business and IT leaders in financial services said the need to provide improved DEX for employees and customers would increase pressure on IT resources. However, nearly half (49%) of financial leaders reported that AI implementations have already optimized resource utilization or will do so within three years, and 94% agreed that AI would help deliver a better digital experience for users. By supporting stretched IT teams, AI implementations can help boost morale.

Other key areas that leaders expect AI will improve includes workflow automation (71%), automated remediation (62%) and autonomously offering 24/7 support via tools like chatbots (62%).

Image
Riverbed-2024-11-3

As IT decision makers increasingly move into C-Suites — 78% said they have a seat at the table — suggesting IT's critical role in driving business innovation is gaining traction. For example, these leaders say technologies such as AI and unified observability are critical to providing exemplary DEX, with 95% saying that unified observability is important (55% said critically important), and 94% calling for greater investment in unified observability solutions.

The next three years will also see a shift toward using AI to drive growth. Currently, leaders say their primary reasons for adopting AI are split almost evenly between operational efficiencies (51%) and driving growth (49%), but 54% expect fueling business growth to be the focus by 2027, ahead of operations, at 46%.

Finally, the survey found that properly implementing AI tools will be essential to boosting productivity, retaining staff, enabling collaboration and staying competitive in the FSI environment.

Mike Marks is VP of Product Marketing at Riverbed

The Latest

As artificial intelligence (AI) adoption gains momentum, network readiness is emerging as a critical success factor. AI workloads generate unpredictable bursts of traffic, demanding high-speed connectivity that is low latency and lossless. AI adoption will require upgrades and optimizations in data center networks and wide-area networks (WANs). This is prompting enterprise IT teams to rethink, re-architect, and upgrade their data center and WANs to support AI-driven operations ...

Artificial intelligence (AI) is core to observability practices, with some 41% of respondents reporting AI adoption as a core driver of observability, according to the State of Observability for Financial Services and Insurance report from New Relic ...

Application performance monitoring (APM) is a game of catching up — building dashboards, setting thresholds, tuning alerts, and manually correlating metrics to root causes. In the early days, this straightforward model worked as applications were simpler, stacks more predictable, and telemetry was manageable. Today, the landscape has shifted, and more assertive tools are needed ...

Cloud adoption has accelerated, but backup strategies haven't always kept pace. Many organizations continue to rely on backup strategies that were either lifted directly from on-prem environments or use cloud-native tools in limited, DR-focused ways ... Eon uncovered a handful of critical gaps regarding how organizations approach cloud backup. To capture these prevailing winds, we gathered insights from 150+ IT and cloud leaders at the recent Google Cloud Next conference, which we've compiled into the 2025 State of Cloud Data Backup ...

Private clouds are no longer playing catch-up, and public clouds are no longer the default as organizations recalibrate their cloud strategies, according to the Private Cloud Outlook 2025 report from Broadcom. More than half (53%) of survey respondents say private cloud is their top priority for deploying new workloads over the next three years, while 69% are considering workload repatriation from public to private cloud, with one-third having already done so ...

As organizations chase productivity gains from generative AI, teams are overwhelmingly focused on improving delivery speed (45%) over enhancing software quality (13%), according to the Quality Transformation Report from Tricentis ...

Back in March of this year ... MongoDB's stock price took a serious tumble ... In my opinion, it reflects a deeper structural issue in enterprise software economics altogether — vendor lock-in ...

In MEAN TIME TO INSIGHT Episode 15, Shamus McGillicuddy, VP of Research, Network Infrastructure and Operations, at EMA discusses Do-It-Yourself Network Automation ... 

Zero-day vulnerabilities — security flaws that are exploited before developers even know they exist — pose one of the greatest risks to modern organizations. Recently, such vulnerabilities have been discovered in well-known VPN systems like Ivanti and Fortinet, highlighting just how outdated these legacy technologies have become in defending against fast-evolving cyber threats ... To protect digital assets and remote workers in today's environment, companies need more than patchwork solutions. They need architecture that is secure by design ...

Traditional observability requires users to leap across different platforms or tools for metrics, logs, or traces and related issues manually, which is very time-consuming, so as to reasonably ascertain the root cause. Observability 2.0 fixes this by unifying all telemetry data, logs, metrics, and traces into a single, context-rich pipeline that flows into one smart platform. But this is far from just having a bunch of additional data; this data is actionable, predictive, and tied to revenue realization ...