Strategies for building AI tools people will actually use at work

The application of generative AI in the workplace is a long game, and we’re in the very early stages. Most businesses looking for ways to leverage AI are in uncharted territory — either experimenting with pilot programs or still exploring ways to meaningfully incorporate the technology into their daily operations. That means the challenge is on for product leaders who are building (or thinking about building) AI tools that employees will actually love and use, whether that’s an app integration, a chatbot, or an AI experience built natively into your existing product offering.

I’ve held numerous product roles throughout my career, but my current work leading the development of Slack’s AI capabilities is my most exciting one yet. Our product teams have kept boots on the ground, listening to what customers care about and thinking hard about how AI can help them meaningfully reach their productivity goals. That’s led us to develop a set of concepts that I believe will help other product teams stay grounded amid all the AI hype and buzz.

Here is a guide that may be helpful for leaders as we build these new products and incorporate large language models into our business strategies and tooling.

Root your gen AI application in users’ needs

An effective way to encourage the widespread adoption of AI tools is to integrate them seamlessly into employees’ existing flow of work.

When building workplace AI tools that resonate with people, the starting point should always be the users themselves. Rather than adopting a broad technology-first approach and asking, “What can we do with AI?” work backward to home in on your core user problems first.

For example, the issues that occur in people’s working lives can vary, but I commonly see complaints of information overload, the inability to optimize or effectively utilize your knowledge corpus, and getting bogged down with mundane to-do lists and tasks that just feel like a waste of time. How can you apply generative AI to solve these user problems and create a more efficient, human, and enjoyable work environment?

Focus on guided experiences

An effective way to encourage the widespread adoption of AI tools is to integrate them seamlessly into employees’ existing work flow. Start with proactively surfacing AI in the moments that it’s most valuable to a person, rather than solely relying on open-ended, user-initiated experiences.

This will allow users at all technical levels to be effective and get the most out of the technology, including those who may not have a familiarity or understanding of how to use AI. Picture instead whether an employee could effortlessly and automatically receive insights and recommendations from AI during team meetings or when analyzing project timelines without having to prompt to get the right answer. By embedding AI into the fabric of employees’ daily tasks, they can harness its capabilities without needing to navigate a steep learning curve, making the adoption process smoother and more intuitive.

Make it clear when AI is involved, and let users interact with it privately

Transparency is a cornerstone of the successful application of generative AI, and indicating when it’s involved builds trust among users. Foster a culture of understanding and confidence in AI in the workplace by flagging AI-generated content.

Appropriately flagged content allows employees to confidently incorporate insights into project decisions, and secure interactions enable them to gradually adapt to and gain confidence around new technology. Additionally, allowing employees to interact with AI privately in a one-on-one setting ensures they can familiarize themselves with the technology at their own pace, building a foundation of comfort before embracing collaborative experiences.

Stay flexible, and don’t replace your employee’s judgment

As the ecosystem of generative AI tools expands, designing flexible and adaptable features that surface when needed, recede when they aren’t, and can always justify the outputs is paramount.

Empowering employees to tweak and verify AI-generated results beyond defaults fosters a sense of control, ownership and trust in the technology. If an employee can tweak the results they receive and check its sources whenever they see fit, then AI becomes a valuable tool, complementing their skills rather than replacing their judgment and expertise.

Integrating generative AI into the workplace is a collaborative effort, requiring thoughtful consideration of user experiences and their needs. As the technology continues to mature in the workplace — moving from basic knowledge retrieval to more advanced capabilities like task automation and proactive trend identification — businesses that focus on guided experiences, prioritizing transparency, and staying flexible are sure to see their tools adopted and embraced by employees and ultimately, reshape how we work.