AI Enablement: Building Cross-team Learning Opportunities

We are working in an era where technological advancements and the integration of artificial intelligence (AI) have become a pivotal aspect of innovation for many organizations. As professionals adapting to the intricacies of AI enablement, the concept of building cross-team learning opportunities emerges as a transformative strategy. Building awareness and understanding around the AI adoption goals and business outcomes promotes collaborations and greater productivity.

"AI success isn’t simply skill acquisition—it needs to become a more sustainable capability within your organization. As you mature, you go beyond what you solve to how well you solve it.” Building a Foundation for AI Success: A Leader’s Guide

Drawing from firsthand experience in designing and implementing AI-based solutions, I delve into the significance of cross-team learning and how it can impact project outcomes with timely innovations and reduce missteps.

A Glimpse into the Journey:

Having dedicated a year to architecting AI-based digital products for a leading fintech organization, I look back on factors that made it a successful and engaging experience. The partnership was structured with equal responsibility across the teams. This is a critical leadership decision that often gets lost in large projects. Each team was in a learning mode: Attempting the first cloud migrations, establishing a data engineering team to enable MLOps, or reimagining a new product vision based on the AI enabled capabilities.

Learning Through Partnerships:

Navigating the intricacies of AI enablement necessitates collaborative efforts across traditional silos. A typical AI projects brings several partners to the discussion table.

Outside the core teams, there are Data office, Legal and Compliance, Security, Marketing, Operations and of course, Finance. Each bring a unique perspective and understanding to the table.

These partners have a vested interest in your project and keeping them in-the-loop, allows them to contribute and gain awareness around the project outcomes as well. They provide context and business interpretations that bear relevance to the model-tuning or ensuring certain compliance tasks are adhered to.

What we did: Using a monthly progress schedule, the AI project team curated the exposure of the design elements to the partners, giving them an opportunity to react, express their understanding and raise concerns, if any. Beyond, the first sessions to get them aware about the AI-led feature design, we were able to build their advocacy.

Using the comparison to the marketing funnel, we were able to convert our -internal clients- around the ideas and principles driving the build.

Win-Win: At the end of the development getting the work approved and certified by the partners was shortened as our transparent communications had mitigated the knowledge gap through the design sessions. The Ai enablement team and our partners both gained from this learning sessions.

Embracing Cross-team Learning for Productivity:

The purpose of building cross-team learning opportunities is to harness the blend of diverse expertise and perspectives that are important to developing solutions with new technologies. By fostering an environment where knowledge-sharing is not bound by departmental confines, organizations can harness the collective intelligence of diverse teams to tackle complex challenges with agility and innovation. This approach not only enhances individual growth but also propels the organization towards sustainable success in an AI-driven era.

What we did: Despite endless hours of sprint reviews, a pattern of unhinged-outcomes became apparent. Missing context not made available was due to lack of awareness on specific processes being used by the enablement team. By creating a more technical design mapping session on a bi-monthly basis, we invited the members of individual squads to join and listen in. Using analogies, use cases, and a no-code approach we explained the context of the development stage to the business outcome and honed into the future needs as well.

Win-Win: The sprint sessions began with the why of the build and how the build would allow for scaling to the full vision. This allowed us build features that would allow product team to expand when data became accessible. This released time and effort for other tasks!

Unlocking the Potential:

Embracing cross-team learning not only cultivates a culture of collaboration but also unlocks untapped potential within organizations. Through knowledge exchange and skill development across the enablement squads we gained problem solving skills with our remote resources. With empowerment and latitude to think, they brought back ideas and solutions to the table. For cross team professionals collaborative learning can broaden their horizons, introduce new domain awareness, and stay abreast of emerging trends in AI and data science being applied within the organization.

This continuous lite upskilling is the starting point for the cultural change within organizations that will sustain long-term relevance in an ever-evolving technology landscape. The learning experience is critical part of organizational change management. This is also a pivotal in moving up the AI maturity curve. While the examples provided are around internal teams, it is equally relevant when it comes to customer onboarding as well. (Mitigating risks with change management and diffusion of innovation strategies)

Looking Ahead:

As we chart the course towards a future where AI integrates into every facet of business operations, the significance of cross-team learning opportunities will keep growing. By nurturing an ecosystem where learning is continuous, collaboration is ingrained, and innovation is valued, organizations can pave the way for a transformative journey towards AI enablement. To emerge ahead as leaders using AI innovations adopting new approaches to training should not be treated as an aspirational goal.

In conclusion, the paradigm of AI enablement hinges not only on technological prowess but also on the collective intelligence and collaborative spirit of diverse teams. By prioritizing cross-team learning opportunities, organizations can harness the full potential of AI, drive innovation, and stay ahead in an ever-evolving digital ecosystem.

If your organization is ready to embark on this transformative journey of cross-team learning and pave the way for a greater collaboration, innovation, and purposeful AI enablement and digital excellence, contact me!

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References:

https://www.hotjar.com/marketing-funnel/

Gartners AI Maturity model explained: https://medium.com/@mohsen.semsarpour/gartner-ai-maturity-model-2c01fab629b6

Building a Foundation for AI Success: A Leader’s Guide