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How Do Startups Build AI Competency Among Team Members?
In the fast-paced world of artificial intelligence, startups are getting creative to stay ahead. We’ve gathered insights from CEOs to CTOs, sharing fifteen strategies to cultivate AI competency within their teams. From initiating weekly AI learn-and-share meetings to nurturing a playful attitude towards AI, explore the fifteen innovative tactics these leaders employ to foster a culture of continuous learning.
- Weekly AI Learn-and-Share Meetings
- Weekly Generative AI Games
- Centralized AI Knowledge Base
- Monthly AI Expert Sessions
- One-on-One AI Mentorship
- Incentivize AI Exploration
- Curate an AI Resource Library
- Create an Internal AI Sandbox
- Structured AI Learning Programs
- Conduct AI Learning Sprints
- Promote AI Certification Incentives
- Structured AI Learning Paths
- All-Employee AI Training Sessions
- Regular Interdepartmental AI Workshops
- Nurture a Playful Attitude Towards AI
Weekly AI Learn-and-Share Meetings
We host a weekly learn-and-share meeting in which we share any interesting and innovative methods we’ve learned or made up in the past week. This includes our use of AI.
This is great because it:
- Provides a free training session for all team members.
- Promotes innovation, which is great for junior employees.
- Allows you to record the session to create a documented training resource.
- Gives you the ability to publish a write-up blog of the session so you get a great piece of content.
Furthermore, we set up an instant messaging channel (we use Slack) to share quick ideas on how to use AI. So, we get a lot of documented ideas through this channel as well. Use the competency of your own team members; the collaborative aspect really helps to build the team!
Will Rice, SEO & Marketing Manager, MeasureMinds Group
Weekly Generative AI Games
At our startup, we’ve implemented a weekly game to help our team get to grips with the concepts and nuances of generative AI tools. We begin each week with the team collectively selecting a random topic, ranging from abstract concepts like “innovation” to more concrete subjects like “sustainable cities.” Throughout the week, team members are encouraged to explore this topic through the lens of generative AI, using the company’s subscriptions to tools such as Midjourney, Adobe Firefly, or DALL-E to create visual representations of their own interpretations and insights on the subject.
The culmination of the exercise is a relaxed, Friday afternoon “AI Showcase” session. Here, each team member presents the image content they’ve created, sharing not only the final output but also the thought process behind their creations. Crucially, they reveal the prompts used to generate their images, providing a valuable learning opportunity for the entire team.
This transparency in sharing prompts allows colleagues to understand the nuances of crafting effective AI instructions, fostering a collaborative environment where techniques and best practices are freely exchanged. The diversity of interpretations and approaches to the same topic also often leads to really interesting discussions, pushing the boundaries of our collective understanding of AI capabilities and limitations.
The impact of this simple strategy on our team dynamics and overall AI skill development has been profound. By engaging with AI tools in a creative, low-pressure environment, team members have rapidly improved their ability to “speak the language” of AI, translating complex ideas into clear, actionable prompts. This skill directly translates to our core work in data analytics and online marketing, enhancing our capacity to leverage AI in practical, innovative ways.
Moreover, the regular sharing of ideas has strengthened inter-departmental collaboration, breaking down silos and encouraging a more holistic approach to problem-solving. As a result, we’ve seen a marked increase in AI-driven initiatives across all departments, with team members more confidently proposing and implementing AI solutions in their daily work. This culture of continuous learning and experimentation has positioned our startup at the forefront of AI integration, driving both our product development and our ability to deliver cutting-edge solutions to our clients.
James Kinsley, Founder, Incendium AI
Centralized AI Knowledge Base
One key strategy we use to build AI competency is by maintaining our centralized knowledge base using Notion. This comprehensive, accessible repository allows all the teams in our company to access essential information, tutorials, and best practices related to AI and other business functions at their convenience. This approach keeps our team motivated to learn and grow, helping us stay up-to-date with AI advancements and apply these effectively in real-world scenarios.
For example, in the marketing team, we utilize AI-driven predictive analytics to analyze customer behavior and tailor our content and offers, which has led to significant improvements in conversion rates. AI has also revolutionized sales forecasting, enabling more accurate predictions based on historical sales data and market trends. However, to fully capitalize on these tools, we integrate human oversight into the process, ensuring a balanced approach.
We encourage our team to leverage specialized AI tools beyond the usual, like ChatGPT or Gemini, which has saved significant time and improved accuracy for us, and we’ve observed increased engagement in training, fostering a culture of continuous learning and innovation.
Kinga Fodor, Head of Marketing, PatentRenewal.com
Monthly AI Expert Sessions
We implement a handful of initiatives to make sure everyone within the company understands AI and knows how to use it the right way. We also have AI incorporated into all of our products—so it’s key that employees understand how it works.
First off, we host monthly “Link n’ Learn” sessions where subject matter experts in the company share AI knowledge like “What are LLMs and How Do They Work?” and “How to Create Effective AI Prompts.” These sessions are recorded, so employees can go back to them for information at any time.
We also encourage employees to learn about AI through Google Cloud’s Machine Learning & AI courses. When an employee completes a course, they get a fun achievement badge that is displayed for everyone to see in Slack. This encourages everyone to participate!
Alexa Franck, Sr. Content Marketing Manager, GoLinks
One-on-One AI Mentorship
In an effort to establish a culture of ongoing learning and creativity among our team, we have created an AI mentorship program. Through paired AI-savvy team members and eager learners, this program facilitates one-on-one training sessions and group projects that apply AI solutions directly to real-world business problems.
To provide individualized development programs that are specifically relevant to their roles, mentees and mentors are matched based on departmental needs and specific learning goals.
To gain real-world experience, participants work on real projects that use AI tools, such as enhancing our e-commerce algorithms or streamlining logistical processes.
We use ongoing feedback and frequent check-ins to talk about progress, modify learning goals, and deal with any new issues that may arise.
In addition to quickening individual learning, this mentoring strategy improves our group’s AI fluency, opening up possibilities for more creative applications of technology at all organizational levels.
Matt Aird, CTO, Custom Neon
Incentivize AI Exploration
I’ve found that the key to building AI competency is promoting a culture of continuous learning. We incentivize our team to explore new technologies through access to online courses and by sending employees to industry conferences.
For example, after attending an analytics summit, two of our data scientists prototyped an AI model to gain insights from customer reviews. They shared their learnings in a company-wide tech talk, and now our marketing team is using the model to improve messaging. This cross-functional collaboration exposes the whole team to AI in action.
We also offer quarterly innovation days where employees can explore side projects using new AI tools. The solutions with the most potential get resources to scale them. This entrepreneurial approach keeps our team excited about the possibilities of AI and at the forefront of advancements in our field.
By providing learning opportunities, encouraging curiosity, and giving employees room to experiment, we’ve built a team passionate about leveraging AI to help our clients succeed. Continuous learning is key to choosing and implementing the right AI solutions for any business.
Russell Rosario, Owner, Russell Rosario
Curate an AI Resource Library
Develop an internal AI library. Curating a repository of AI books, articles, and courses provides team members with easily accessible resources for continuous learning, essential in the evolving world of finance.
Advisors can use this resource to explore AI-driven insights for risk management, portfolio optimization, or tax planning strategies. By staying updated on these advanced tools, the team can offer more tailored financial advice based on predictive algorithms and machine learning models. This helps the firm deliver a superior client experience while optimizing investment strategies.
In the long run, building AI competency supports the firm’s growth by ensuring that advisors are prepared for the future of AI in finance.
Shawn Plummer, CEO, The Annuity Expert
Create an Internal AI Sandbox
We’ve created an internal AI sandbox, where team members from any department can experiment with AI tools, even if they don’t have a technical background. This safe space encourages people to play around with AI applications—whether it’s using GPT to streamline content creation or leveraging machine learning to analyze user behavior on our platform. It removes the intimidation factor and builds a foundation of hands-on experience. We’ve seen incredible cross-functional learning happen here, as marketing, product, and even HR dive into AI without fear of failure.
Mark McDermott, CEO & Co-Founder, ScreenCloud
Structured AI Learning Programs
At my startup, we prioritize building AI competency through structured learning programs that combine online courses with hands-on projects. We’ve partnered with platforms like Coursera and Udacity to provide our team members access to high-quality AI training tailored to their skill levels. Each employee sets personal learning goals related to AI technologies relevant to their roles, ensuring that the training aligns with both individual interests and company objectives.
To foster a culture of continuous learning, we also encourage knowledge sharing through regular lunch-and-learn sessions where team members present what they’ve learned or showcase projects they’ve completed using AI techniques. This not only reinforces their learning but also inspires others to explore AI applications in their work.
Azam Mohamed Nisamdeen, Founder, Convert Chat
Conduct AI Learning Sprints
Implement AI learning sprints. AI learning sprints are focused, deep dives where your team dedicates time to exploring the latest AI tools, research, and methodologies. The sprints can be conducted bi-weekly or monthly. During our bi-weekly AI learning sprints, we pair data scientists, engineers, and non-technical staff with different AI technologies to experiment and share their findings with the rest of the team. We rotate focus areas so that everyone has a chance to cross-train in diverse AI technologies.
The hands-on approach helps our team build technical competency and encourages collaboration. The key to success is keeping your learning sessions flexible and self-driven. Let every team member choose their learning path and support them. Those who want to learn through development should be allowed to participate in internal hackathons, while those who wish to learn through academic understanding should have access to high-quality AI courses.
Mitchell Cookson, Co-Founder, AI Tools
Promote AI Certification Incentives
Encouraging team members to pursue AI certifications strengthens the overall technical capabilities of the team.
As individuals gain expertise in AI, they’re better equipped to collaborate on AI-driven projects, share insights, and find creative solutions. This collective knowledge enhances problem-solving abilities across the board, leading to more efficient workflows and better project outcomes.
Providing incentives for certifications also motivates employees to stay current with technological advancements. In turn, this investment in skill development drives the team’s ability to remain competitive and innovative in a fast-paced industry.
Albert Kim, VP of Talent, Checkr
Structured AI Learning Paths
One of the main strategies we use to build AI competency in our team is creating a structured AI learning path that fits right into our daily work. This path includes team members and guest experts with hands-on AI experience.
We focus on practical AI applications by encouraging everyone to leverage AI in their workflows. Whether testing out machine learning algorithms or working with AI-powered tools for data analysis, team members gain real-world experience while learning AI skills.
We also set up a buddy system where AI developers mentor newer members. This makes learning faster and creates a collaborative environment. Moreover, we encourage everyone to experiment with the latest AI platforms and tools to stay updated.
By combining learning with real project work, we’ve built a culture where AI skills grow naturally, helping our team stay confident and up-to-date with AI.
Aditya Dash, Data Scientist, Wavel AI
All-Employee AI Training Sessions
My company has viewed the deployment and adoption of AI through the lens of a startup because the technology is rapidly evolving, and we are looking for opportunities to bring value in faster decision-making, greater efficiency, and automation to the company. These are untapped opportunities, and for the first time, we have the tools to achieve them with AI.
We have held a series of all-employee training sessions to help upskill our teams, give them prompt engineering strategies, and practice ways they can use the technology to “win back time.” As a result of these trainings, we have seen our employees launch into new ways to apply AI, and personally find ways to use our GenAI assistant to improve their work.
Nate Melby, VP and Chief Information Officer, Dairyland Power Cooperative
Regular Interdepartmental AI Workshops
What works for us is holding regular AI workshops for all departments. This means that we try to boost AI knowledge not only among teams that already work with AI but also we encourage those teams to improve their skills and to share their experience with other departments. We bring together developers, data scientists, and even designers to learn about AI.
Plus, they often bring in fresh vision, which we can later adapt and integrate with our AI specialists. For example, we once had a workshop where our teams developed AI-driven predictive analytics for one of our projects, which allowed everyone to contribute based on their expertise.
Pavlo Tkhir, CTO at Euristiq, Euristiq
Nurture a Playful Attitude Towards AI
We’ve developed a distinctive strategy to build AI competency among our team members, fostering a culture of continuous learning and mutual trust. Central to our approach is nurturing a playful and curious attitude toward new technologies. We encourage our team to experiment freely, exploring the possibilities of AI without the fear of making mistakes. This hands-on exploration is crucial because we believe that true innovation arises from the freedom to test boundaries and discover new solutions.
Fostering mutual trust is fundamental to our culture. We create an environment where team members feel safe to take risks and share ideas openly, knowing that their contributions are valued and respected. This trust empowers our team to delve deeper into AI technologies, confident that they have the support of their colleagues and the organization. By trusting one another, we enhance collaboration and accelerate our collective learning.
We embrace the idea that breaking things is part of the learning process—as long as they can be repaired. This approach allows our team to gain a deeper understanding of AI systems by dissecting and reassembling them. Through this iterative process of trial and error, our team members develop the confidence and expertise needed to excel in the rapidly evolving field of AI.
Maintaining a natural skepticism toward automating creative tasks is another key aspect of our strategy. This skepticism doesn’t hinder us; instead, it drives us to critically evaluate how AI can enhance rather than replace human creativity. By thoughtfully integrating AI into our creative processes, we ensure that technology serves as a tool to amplify our ideas, not diminish them. This careful balance helps us harness the power of AI while preserving the unique human touch that defines our work.
Moreover, we prioritize action and implementation over prolonged planning. By swiftly transforming ideas into tangible prototypes and demonstrations, we keep the momentum alive. This practice not only validates our concepts in real-world scenarios but also keeps the team engaged and motivated.
Through this multifaceted strategy, we’ve cultivated an environment where continuous learning is ingrained in our daily operations. Mutual trust among team members enhances open communication and collaboration, allowing us to leverage our collective expertise.
Magnus Høholt Kaspersen, PhD, Partner and AI Expert, Creative Oak
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