Put trust infrastructure before intelligent automation for better collaboration

Astute leaders recognize that many times, automation and technology failures aren’t really about the technology itself. Rather, failures occur because the necessary underlying infrastructure linking people, processes, and technology isn’t in place. For example, consider organizations that try to partner together but don’t take the time to align their tech implementations in a way that match the real-world outcomes they want to achieve. Without trust infrastructure and meaningful alignment, such collaborations are doomed to fail.

Creating a foundation of trust

AI adoption brings its own unique opportunities and challenges to both internal and external collaborations, especially in the way it disrupts existing workflows and encourages new forms of risk-taking.

An analysis by the Center for Creative Leadership notes that leaders should build cultural foundations of trust so new technology implementations strengthen rather than erode that trust. Creating psychological safety in the workplace occurs when leaders model learning rather than feign certainty about AI changes, and seek honest involvement and feedback from team members while being transparent about intentions and trade-offs associated with AI use.

After all, it’s hard to build a cultural trust infrastructure when one day everyone’s told how much they’re valued, and the following day, thousands are laid off because of AI restructuring.

When your internal team can’t trust your approach to intelligent automation, outside organizations you partner with may also develop trust barriers. How can they trust your organization to treat them fairly and with transparency if they’re concerned you’re planning to use tech in a way that will undermine a partnership?

Extending trust to digital spaces

In addition to using the foundation of cultural trust in communicating efforts to implement AI, the idea of trust can directly impact how these tools are used and set up. Because of this, intelligent automation needs a solid trust infrastructure in place to succeed. Partners sharing digital resources need to clearly define how they configure and manage their tech, as well as the real, measurable KPIs they want to achieve through implementation. Processes and procedures for sharing data in a secure and timely manner gives both sides the necessary information to leverage tech in the way intended.

A lack of trust — particularly fear of the unknown — can often undermine cross-enterprise collaborations, and this is especially true of tech implementations. A shared foundational infrastructure helps improve cultural trust through increased transparency, which in turn can improve buy-in among the individuals who interact with that tech on a day-to-day basis.

Digital trust infrastructure also enables AI tools to be more effective, so when team members interact with the AI to get insights, recommendations, or data reports, they can trust what the tech tells them. Instead of trying to create their own workarounds to avoid using the tools, they become adopters and promoters, closing the gap in data and insights that so often plague other collaborations.

AI won’t fix what’s broken

Unfortunately, many organizational leaders seek AI implementation to be a cure-all for problems. Astute leaders recognize if their organization doesn’t have a solid trust infrastructure in place, AI will magnify those problems, not fix them.

“Think of AI as a piece of world-class, designer furniture,” says Jary Carter, co-founder and CRO of B2B-focused commerce platform OroCommerce. “If you put a $20,000 Italian sofa in a home filled with clutter, dust, and bad flooring, it doesn’t make the house look better. It just further highlights your mess. In business, that mess is legacy systems, fragmented data, and siloed teams. If you haven’t built a unified digital infrastructure first, AI will only accentuate your flaws. It also won’t improve your customer experience by highlighting inefficiencies directly to customers.”

While throwing AI at existing data gaps won’t solve your collaboration problems, the automation isn’t necessarily to blame. Trust-building needs to happen alongside tech implementations because otherwise, the right data won’t be shared, people and machines won’t have access to the info they need, and the entire collaboration will falter.

Laying the foundation for better collaboration

The emergence of gen AI means that when we talk about trust infrastructure, we can no longer consider cultural and organizational trust alone. Leaders must also consider what that trust infrastructure looks like for their digital applications and automations.

By taking proper steps to build a dependable infrastructure based on transparency, aligned values, and clearly defined goals, leaders can increase their digital trust. This will yield greater buy-in of automated intelligence within the organization, and improve its applications during cross-enterprise collaborations.