Why are finance teams not using AI to harness real-time data?
CFOs admit their finance team are struggling to harness the full potential of their data in real-time but could AI be the solution?
Artificial intelligence and real-time data are poised to disrupt financial services operations, according to a new industry study. The research, conducted by ActiveOps, found that 81-84% of operations leaders believe that AI-enabled real-time data would significantly improve key areas such as customer experience, employee engagement, operational performance, and decision-making.
As institutions grapple with outdated systems and data challenges, this widespread optimism signals a potential turning point for the sector.
The financial services industry has long recognized the importance of data-driven decision-making. However, the ActiveOps study, which surveyed over 850 Chief Operating Officers, Chief Financial Officers, and Senior Heads of Operations across seven countries, unveils a stark reality: many organisations are struggling to harness the power of their data effectively.
Despite the acknowledged importance of data, 91% of respondents report that it takes significant effort to extract insights from their operational data. More alarmingly, 94% are not utilizing real-time data in their operations.
This data deficit has a tangible impact on decision-making processes, with 97% of leaders facing challenges in operational decision-making. Many are basing critical decisions on data that is weeks or even months old, potentially compromising the accuracy and timeliness of their strategies.
The Promise of AI
Amidst these challenges, there’s a palpable sense of optimism about the potential of AI to transform operations. The 81-84% who believe in the transformative power of AI-enabled real-time data anticipate improvements across multiple facets of their operations:
- Customer Experience: Real-time data could enable more personalized and responsive service.
- Employee Engagement: AI could streamline processes, reducing mundane tasks and allowing staff to focus on higher-value activities.
- Operational Performance: AI-driven insights could identify inefficiencies and optimize processes in real-time.
- Decision-Making: Access to real-time, AI-processed data could support more informed and timely decisions.
However, the adoption of AI in financial services operations is still in its early stages. The study reveals that 49% of organizations are either just starting out with AI or not using it at all. Only 15% report using AI at an advanced level, indicating significant room for growth and improvement across the industry.
The Path to AI Transformation
As financial services leaders look to the future, they anticipate several key benefits from AI adoption:
- Enhanced Cybersecurity Control (39% of respondents)
- Improved Real-Time Decision Making (39%)
- Access to Deeper Insights (35%)
However, the path to AI transformation is not without obstacles. A staggering 98% of respondents face challenges in adopting AI. The primary concerns include:
- Job Displacement (37%)
- Ethical Considerations (36%)
- Lack of Infrastructure (29%)
These figures highlight the need for a balanced approach to AI implementation, one that addresses both technological and human factors.
The Future of AI-Driven Operations
Despite the challenges, there’s a growing appetite for increased AI involvement in operations. 36% of leaders express a desire for AI to take action based on predictive insights, while 40% want AI to provide suggestions based on these insights. This shift towards more autonomous AI systems represents a significant evolution in how financial services operations may function in the near future.
Resources & Whitepapers
Accounting Software The power of customisation in accounting systems
However, the key to unlocking AI’s potential lies in data readiness. Organizations must prioritize the development of robust data infrastructure and ensure data quality to fully capitalize on AI capabilities. This may involve investments in data management systems, training for staff, and the development of clear data governance policies.
Why now?
For CFOs and senior financial leaders, the message is clear: investment in AI and data infrastructure is not just about keeping pace with technological trends—it’s about positioning your organization for future success.
Those who successfully navigate this transition will likely find themselves at the forefront of the industry, while those who delay may struggle to catch up. As you consider your organization’s future, ask yourself: are you ready to harness the power of AI-enabled real-time data?
