Navigating the digital shift: Cloud, Data, and AI in the Financial Services industry

FStech and Rackspace Technology are surveying financial services professionals to explore the challenges and opportunities they are facing when adopting secure, resilient, and scalable cloud environments and emerging AI strategies in order to drive innovation and business value.

Questions

1. What are the primary drivers of your organisation's cloud, data, and AI initiatives? [select top three]

Staying ahead of the competition
Enhancing customer experience
Reducing operational costs
Improving efficiency
Simplifying and reducing technical debt
Increasing business agility to reduce time-to-market for new products and services
Catching up with the market

2. What key performance indicators do you use to measure the success of your cloud, data, and AI initiatives? [select all that apply]

Return on Investment (ROI)
Cost reduction metrics
Operational efficiency improvements
Customer Net Promoter Score (NPS) (i.e. Asking customers to rate the likelihood that they would recommend a company, product, or a service to a friend or colleague)
Revenue growth
Time-to-market for new products/services
Improved regulatory compliance metrics
Employee NPS (eNPS) (i.e. Gauging staff satisfaction to monitor buy-in of new technologies)

3. What are the biggest challenges you face in obtaining the best value from technology? [select top three]

Business objectives or focus changed
Effective deployment of technology
Unexpected costs or programme over-runs
Lack of leadership sponsorship or turnover of leadership
Lack of budget or initial investment
Integration issues given technical debt and/or complex architecture
Lack of resources or skills

4. What role does AI play in your organisation's customer service and engagement strategy? [select all that apply]

AI-powered chatbots and virtual assistants for front-line customer service
Predictive analytics for personalised customer experiences
AI-driven sentiment analysis for customer feedback
Using AI for proactive customer outreach and engagement
Automated decision-making for routine customer requests
Exploring AI applications but not yet implemented
Dynamic routing of work leveraging AI
No current plans to integrate AI into customer service

5. How are you future-proofing your data strategy and infrastructure to handle anticipated growth while maintaining performance, security, and cost efficiency? [select all that apply]

Enterprise agile innovation model with executive support and multifunctional team focussing on specific business journeys
Innovation panel for ideation, and sponsorship
Decentralised innovation approach with dedicated teams building new capabilities
Localised experimentation without enterprise-wide coordination
Comprehensive planning and stakeholder approval process

6. How is your organisation managing the transformation to cloud, data, and AI technologies? [select all that apply]

Dedicated change management team executing a structured programme with defined OKRs
Comprehensive change programme with executive sponsorship, addressing all aspects of the new operating model
Ambassador programme facilitating adoption and ensuring long-term sustainability of changes
Implementing lessons learned through a targeted improvement programme
No perceived need for alterations to current methodologies or governance structures

7. How would you characterise the maturity and efficacy of your business case for cloud, data, and AI initiatives? [select one option]

Managed with proactive executive support and associated interventions, consistently meeting or exceeding expected benefits
Regularly reported with minor deviations from projected benefits across people, process, and technology
Regularly reported with significant deviations, necessitating strategic revisions
Under review due to unforeseen costs or missed projections
No longer relevant and requires comprehensive reassessment

8. What are the primary obstacles you face in realising your business goals related to cloud, data, and AI initiatives? [select top two]

Insufficient executive-level support or alignment
External factors altering the business landscape
Prolonged regulatory compliance processes
Lack of internal expertise for strategy development and implementation
Legacy systems impeding significant new investments
Strategic uncertainty regarding initiative commencement
Internal challenges in aligning security, risk, and compliance requirements

9. How is your organisation addressing talent acquisition and skill development for cloud, data, and AI initiatives? [select all that apply]

Comprehensive strategy encompassing reskilling, succession planning, strategic hiring, and partnerships
Clear strategy with plans to rebalance internal and external resources through strategic insourcing and partnerships
Facing challenges in talent acquisition and retention due to market competition
Seeking assistance in developing the required capabilities
Investing in continuous learning and development programmes for existing staff
Partnering with educational institutions to develop tailored training programmes

10. How does your organisation balance innovation imperatives with regulatory compliance in cloud and AI initiatives? [select all that apply]

Implementing a compliance by design framework across all initiatives
Engaging in regular dialogue with regulatory bodies on innovative projects
Utilising sandboxes for controlled testing of new concepts
Establishing strategic partnerships with RegTech firms to ensure compliance
Concentrating innovation efforts in less regulated domains
Prioritising regulatory compliance over innovation
Actively working to establish an optimal balance

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