3 Steps to Building a Culture of Learning and Innovation Around AI

Integrating a fast-moving technology like AI into your business requires thoughtful leadership. Our expert explains how to make your company culture flexible and receptive to it.

Written by Ted Lango
Published on May. 15, 2024
3 Steps to Building a Culture of Learning and Innovation Around AI
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AI is more than a handy tool – it’s a catalyst for innovation. As organizations strategically incorporate AI into their operations, achieving success hinges on not only mastering the technology’s sophisticated capabilities, but also cultivating an environment that fosters curiosity, creativity, and a willingness to embrace change. This blend of technology and culture is transforming how businesses innovate and compete in a rapidly evolving digital landscape.

Businesses will find the greatest AI-driven impacts when the technology is used to streamline operations, enhance productivity and enable creativity. But before a company achieves these benefits, leadership must lay the groundwork to help their employees embrace the technology. Consider these three steps for building a successful AI-driven culture. 

3 Steps to Building a Culture of Learning and Innovation Around AI

  • Embed AI as a strategic pillar.
  • Promote acceptance, learning and innovation.
  • Don’t overlook soft skills.

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Embed AI as a Strategic Pillar

Businesses that rely on data and technology must adopt AI not as just another tool in the toolbox but as a core strategic pillar. Senior executives must lead the way with intentional effort and active involvement in moving others along the AI learning curve. Top-down engagement will showcase a genuine commitment to embedding AI into the organization’s DNA, making it clear that AI is integral to the company’s future.

All levels of leadership need to participate actively in AI initiatives. The truth is, though, this participation won’t always happen without a company-wide decision to dive head-first into AI.

One strategy might be for leadership to ask each department to choose one metric they want to move quarterly using AI-enhanced technology. For example, customer service could look to cut down on the time it takes to resolve a customer’s issue via chatbots, or IT could use it to debug an application more efficiently. Sometimes they’ll succeed, while others they’ll find their chosen tool doesn’t accomplish enough. That’s OK: It’s the process of embracing and exploring the technology that shifts mindsets.

So, what types of tools should departments look at to move the needle?

For frontline roles, departments should be encouraged to experiment with generative AI tools — creating and refining prompts for customer-facing documents, supporting editing processes and handling basic customer service tasks. For the tech-focused or product development teams, the approach might go a few layers deeper, such as coding AI platforms.  This could mean learning or upskilling on programming languages such as Python, R, and Java, and techniques such as data cleaning, normalization, and feature extraction. To get these teams up to speed, leaders must engage in regular training, incentivized skill development and one-on-one mentoring and coaching.

When all departments are engaged with AI in a manner that makes sense for their roles and have a little push to incorporate these tools into their strategy, AI becomes a shared responsibility rather than a siloed function. 

 

Promote Acceptance, Learning and Innovation 

Although goals and objectives are extrinsic motivators toward greater AI adoption, building an AI-driven culture must involve intrinsic motivators as well. Company leaders need to foster an environment that values continuous learning and curiosity. That means providing access to educational resources, training programs, and workshops focused on AI and its applications. 

At my organization, Intradiem, we schedule one lunch per week to discuss what’s new in AI. We wouldn’t want the frequency to be any less than once a week, as AI is constantly evolving and continuously throwing new curveballs at B2B technology companies. We begin with a brief introduction to a new tool or updates to an existing one, then leave much of the lunch for open conversation and experimentation. This offers a level playing field for candid discussions on how best to use the technology within our organization and helps employees feel more comfortable about learning a new AI-driven skill.

There are two keys to helping employees find personal value in these conversations. First, being particular about who leads the conversation will greatly impact how beneficial the discussion is. The facilitator shouldn’t be an IT leader who will speak in a language that could quickly lose newcomers. Instead, choose someone with an engineering mindset. This means someone who is curious about how to strip these tools down to their virtual parts and who is good at explaining how they work. This will make the technology less intimidating.

Two, conversations should be cross-departmental, as should any decision-making body around AI. This strategy can help employees in different roles look at AI tools with various perspectives and offer their own unique insights into how their colleagues can solve a perplexing issue. These a-ha moments really fuel the desire to learn further.

One other note: Don’t forget the power of recognizing AI integration achievements whenever possible. Celebrating even minor successes and rewarding teams for innovative ideas will encourage ongoing engagement with AI. Recognition programs can highlight the transformative impact of AI projects, showcasing how they contribute to organizational goals and success.

 

Don’t Overlook Soft Skills 

While leadership is training employees on how to best leverage AI programs, it’s just as important to re-emphasize the skills that serve as the bedrock for all business activities. AI projects often require navigating complex ethical considerations and making decisions that impact the organization and, potentially, society at large. That’s why emotional intelligence, critical thinking, and collaboration across diverse teams remain indispensable attributes. For example, if an AI program is developed using incomplete or biased training, it will ultimately offer poor or even discriminatory customer service.

The best strategy for prioritizing soft skills in AI development is for leadership to promote a people-first mindset. You should first weigh every business decision by how it will impact the company’s employees and customers. When leadership shows this commitment and people-first approach in action, it will trickle down and disseminate to the entire workforce, creating an organization that is conscious of how business and technical decisions affect one another. 

Finally, never allow employees to rest on their laurels. AI will continue to evolve, so the employees’ soft skills need to grow as well. Encouraging continuous education and a culture of curiosity will ensure that teams remain at the forefront of technological advancements.

Rather than requiring employees to find their own courses and pay their own way, organizations can include memberships to online programs such as MasterClass and LinkedIn Learning as job perks. They can also set aside time in all-hands meetings for team members to share what they’ve learned. When professional development becomes engrained in company culture, there’s likely to be less resistance to the integration of new AI-driven technologies. You’ll also likely see more thoughtfulness in developing and rolling out smart tools.

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Lead From the Front

The importance of leadership’s role in promoting an AI-positive culture cannot be overstated. Leaders should advocate for and model an AI-centric mindset, giving their team both extrinsic and intrinsic motivators to embrace AI, while supporting their team as they develop the skills necessary to refine AI solutions. By leading from the front, leaders can inspire their teams to embrace AI, emphasizing its potential to enhance their work and the organization’s broader mission.

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