Rolling out Artificial Intelligence (AI) internally can deliver quick, impactful wins and drive significant efficiency, but leadership teams may often struggle to determine where to start. Competitors are already taking action, with McKinsey reporting a surge in AI adoption to 72% in 2024.

At my digital banking company Alkami, we focused on identifying key use cases for Generative AI (GenAI) across all functions, enabling us to deploy the technology safely and effectively. Here are important lessons we learned about scaling GenAI today.

Strategies for scaling AI successfully

To approach GenAI in a way that balances potential long-term benefits with short-term gains, project leaders should start with a discovery journey. Engage with employees across the organization to learn how they are currently using AI and where they see its potential. The insights you uncover can often be educational, with a vast array of use cases spanning work within different departments and levels of employees.

For example, at my digital banking company, this exercise revealed over 140 use cases, including several surprising ones. While technical teams were expected beneficiaries, other departments like marketing and client services also showed great potential for automation and data insights. For instance, marketing departments and client service teams, who handle numerous inquiries daily, could profit greatly from more efficient workflows and reduced repetitive tasks.

While discovery is crucial, securing C-suite support early is equally important for long-term success. This can help enhance company-wide engagement with new systems and processes while factoring in specialized perspectives that may uncover obstacles before they arise. During my organization’s discovery efforts, our chief compliance officer participated in understanding AI use cases and assessing potential data exposure, ultimately helping us shape more informed policies.

These policies directly influenced vendor selection. A thorough requirements list helps organizations avoid reliance on generic, off-the-shelf solutions that may not align with company needs. Instead, conducting a comprehensive vendor analysis can help future-proof technology solutions with scalability needs such as architecture, compression, workload management, performance monitoring, and storage, to name a few key factors. Working with a vendor that treats the relationship like a partnership, rather than simply a transaction, can also provide more assurance for the long term.

Once opportunities and needs are established and vendors and tools are selected, budgeting for scalable GenAI solutions encompasses expenses that go beyond the initial implementation.

Leaders should build and implement a budget process that anticipates costs for new technologies, platform upgrades, and emerging security threats. While leaving budget management to finance officials can be tempting, this exercise can be more effective as a cross-department responsibility. Demonstrating scalable return on investment is essential for securing ongoing funding or highlighting solutions that can be consolidated to make room for newer technologies.

GenAI initiatives need company-wide training on AI policies and best practices to scale effectively. In addition to initial training exercises to acquaint users with the new technology, leaders should arrange for ongoing training to cover new feature releases and to ensure everyone is current on the latest compliance policies.

Approaching compliance with a scalability mindset

Compliance with governance, ethics, and privacy regulations is foundational to any GenAI endeavor. Executives should establish a baseline compliance policy to ensure all AI activities meet core governance, ethics, and privacy standards. While protocols may be viewed as an internal initiative, they are driven by external factors including state, federal, and even international mandates.

To stay current, a base compliance policy can be regularly monitored and maintained as a joint effort that includes but is not exclusive to, a legal team. My digital banking company formed its own AI governance committee to bring in representatives with different areas of expertise such as security, compliance, and product. Include senior leaders like the chief legal officer, chief compliance officer, chief technical officer, and AI specialists in governance working groups.

These stakeholders can work together to evaluate the organization’s acceptable risk level and the data that will be processed using AI to align compliance efforts.

A clear, well-defined plan helps leadership teams implement scalable GenAI solutions aligned with the company’s long-term goals. Defined goals and use cases can help with selecting the right hardware, architecture, monitoring, and security protocols that can grow with the organization and as the technology inevitably expands in capability and practicality. Staying updated on GenAI trends and guidelines positions companies to integrate emerging solutions seamlessly into existing infrastructure.

Long-term scalability comes with regular review of the technology and defining what success looks like with measurable results. Having a framework to follow will allow for adjustments and new experimentation along the way, to be certain the organization is gaining efficiencies and using the AI tools to their potential.

About the Author:

Matt Wilson is an experienced technology and operations leader with over 20 years of expertise driving digital transformation across various industries. He is currently the Vice President of Strategic Initiatives at Alkami, a leading digital banking provider in the U.S. In this role, Wilson steers cross-functional teams to develop and deliver innovative solutions that enhance business performance, optimize operations, and accelerate growth.

He has successfully guided organizations through complex technology and operational projects, enabling them to implement scalable, measurable results. Wilson is recognized for his contributions to the digital banking sector and has received multiple awards for designing innovative solutions that improve user experiences coupled with best-in-class performance.

With a strong strategic vision and results-oriented leadership style, Wilson excels in fostering collaboration, driving operational excellence, and inspiring innovation. He is committed to leveraging emerging technologies to support organizational growth and deliver transformative outcomes for businesses and their stakeholders.