AI Strategy Development

The AI Imperative: Act Now or Fall Behind

Every company is incorporating some level of AI.   The business landscape is being reshaped by large investment in AI empowered tools.  But using AI tools is only the beginning of AI empowerment.  Senior Leadership must quickly create a comprehensive and forward-looking AI foundational strategy which incorporates and enhances current business growth models, effective risk management, internal controls and cost savings. 

Building an effective AI Strategy is no easy task. A leadership team must accept three factors which are at the heart of an AI strategy:

Competitive Necessity

AI will fundamentally change your operating model – making it more flexible, efficient, and cost-effective but it will be very different from your current model.

Skill Gap Crisis

AI expertise must be built across your organization immediately to remain competitive.  The search to find and retain talent is critical;

Disruptive Reality

AI is a watershed: it is disruptive by nature. It will change what you do and how you do it.  It will not be embraced by all in your institution.  You must accept AI and harness it, or be disrupted by competitors who accept the disruption and move forward. 

 
 

Industry Statistics

99%

of financial institutions are deploying AI in some capacity
(Source: EY 2023 Financial Services GenAI Survey)

$200-340B

annual value potential for banking from generative AI
(Source: McKinsey Global Institute

$85B 

projected banking sector spending on generative AI by 2030
(Source: Statista/Juniper Research)


The First Step: Building an AI Adoption Strategy

AI is still in its formative stages.  An organization’s first step is to build an AI Adoption Strategy, the foundation upon which AI strategy and growth is positioned for the future.  We will assist you in developing a comprehensive AI adoption strategy that leverages your institution’s ability to take full advantage of AI in a controlled manner, now and in the future. 

Key Elements of an AI Adoption Strategy:

  • Enterprise-Wide Governance:  the creation of an AI utilization inventory upon which we create an AI Enterprise Governance program with clear accountability, risk management protocols, technology input, regulatory compliance measures and audit controls;    
  • Risk Management:  a comprehensive enterprise-wide risk framework which addresses the overarching risks of AI to the organization, the risk evaluation of proposed AI tools and systems and the identification of specific AI risks such as bias, explainability, privacy and regulatory compliance;
  • Strategic Use Case Selection: In the current growth stage of AI development, AI must supplement your business model, not replace it.  We will identify and prioritize AI opportunities that align with your business strategy, deliver measurable ROI and deliver maximum business value to your current strategy.   Note the listing of current and future AI initiatives below.
  • Technology Integration: AI strategy requires a seamless integration with existing infrastructure and data governance. We develop comprehensive technology roadmaps that integrate AI seamlessly into your existing infrastructure, ensuring scalability, security, and operational efficiency.  This includes architecture design, data governance, system integration, performance optimization.

The Road Ahead: Can you afford to wait?