December 16, 2021

3 min

Aligning Stakeholders for Better AI Outcomes

Increased collaboration and communication will enhance your enterprise artificial intelligence practice.

Education and communication are essential for organizations that bring artificial intelligence into their operations. Teams that lack experience with AI or don’t understand its potential are more inclined to push back against efforts to bring AI into workflows and decision-making. Cultural leadership can help to bridge this gap, especially in organizations that historically have been siloed. 

A big part of AI’s value is its ability to bring different aspects of a business together to obtain 360-degree insights. Getting the most out of an organization’s data requires stakeholders to break down siloes so they can share knowledge and experiences. Executives who facilitate collaboration and communication will put their teams in a better position to embrace and leverage AI.

As a first step, think about who should be involved in these projects. Stakeholders represent different parts of a business, each with a unique perspective. Together, they form a well-rounded team that can move AI initiatives forward.

Leveraging AI to Reduce Cost, Improve Experience and Minimize Risk

Success starts at the top, where high-level executives focus on broad outcomes: saving money, improving the customer experience and minimizing risk. They’re asking, “What’s the return on investment?” and “How can we become a data-driven company?” 

In this case, part of the culture shift is increasing agility by learning to fail quickly. Leaders should aim to get the most out of any initiative, then align assets and resources that can accomplish key goals. With AI, that means understanding the scope of the project and ensuring the organization has the data it needs to drive these initiatives. At the end of the day, leaders need to be clear on the benefits they expect to obtain.

AI Insights Drive Innovation and Market Differentiation

One layer down, project leads or managers are leveraging AI for innovation. How can they use the benefits of cost, experience and risk to differentiate their organization from its competitors?

Project leads often ask how to use AI tools to improve outcomes in business units, especially when stakeholders are resistant to change. One of the questions I hear most is, “How do I get people off an Excel spreadsheet?” 

My advice is to have a conversation. Leaders should understand which tools the stakeholders are comfortable with and figure out ways to boost their comfort with new processes. This could mean using an AI model on the back end and presenting data to stakeholders in Excel and Tableau, for instance. 

What’s important is finding a way to bring in disparate data sources that can enrich stakeholders’ contributions and innovations.

Collaboration Leads to Deeper AI Analysis and Insights

Additional stakeholders will depend on the data pipeline, as reflected in the initial scoping. 

Anyone who touches the data in any way — through storage, computing, transformation, delivery, development insights and so on — should be involved. The team needs to think about how a particular workflow affects stakeholders and, in turn, how they can contribute to its success. 

Bringing business units together supports the overall effort to reduce siloes. Maybe the marketing team has information that the sales department doesn’t, or vice versa. Better collaboration — with both people and data sources — allows an organization to ask deeper questions of data and reach true insights.

Story by Tom Leinberger