How can you encourage collaboration and learning across AI and business intelligence teams?

1 Align on objectives and metrics

The first step to bridge the gap between AI and BI teams is to align on the objectives and metrics that matter for the business. This means defining clear and measurable outcomes, such as revenue, customer satisfaction, or efficiency, and how they are influenced by AI and BI initiatives. It also means establishing a common language and framework to communicate and track progress, such as dashboards, reports, or KPIs. By aligning on objectives and metrics, AI and BI teams can avoid duplication, confusion, and conflict, and focus on delivering value.

4 Solicit feedback and iterate

The fourth step to enhance collaboration and learning across AI and BI teams is to solicit feedback and iterate. This means collecting and analyzing feedback from various stakeholders, such as customers, users, or managers, on the performance, usability, and value of the data-driven solutions and experiments. It also means applying the feedback to improve, refine, or pivot the solutions and experiments, based on the data and the objectives. By soliciting feedback and iterating, AI and BI teams can ensure that their solutions and experiments are aligned with the needs and expectations of the business and the market.

5 Celebrate successes and learnings

The fifth step to encourage collaboration and learning across AI and BI teams is to celebrate successes and learnings. This means recognizing and rewarding the achievements, contributions, and learnings of both teams, such as delivering a successful solution, solving a challenging problem, or discovering a new insight. It also means sharing the successes and learnings with the wider organization, such as through presentations, newsletters, or blogs, to showcase the value and impact of AI and BI. By celebrating successes and learnings, AI and BI teams can build confidence, motivation, and reputation, and inspire others to join the data-driven culture.

6 Invest in training and development

The sixth step to foster collaboration and learning across AI and BI teams is to invest in training and development. This means providing both teams with opportunities and resources to learn new skills, tools, and techniques, such as online courses, workshops, or mentors. It also means creating a supportive and inclusive environment, where both teams can share their knowledge, challenges, and best practices, and learn from each other. By investing in training and development, AI and BI teams can enhance their capabilities, broaden their horizons, and stay updated and relevant in the fast-changing data landscape.

7 Here’s what else to consider

This is a space to share examples, stories, or insights that don’t fit into any of the previous sections. What else would you like to add?