AI Evangelism in Corporate America

How is your organization thinking about AI? I’ve found that there are 3 common scenarios:

1. My company has a dedicated innovation group, or IT department of significant size that is actively investing in AI discovery.
2. My company does not have a dedicated team investigating the potential of AI, but we have interested individuals in various departments, who have started to experiment with it.
3. My company is not looking at AI at all. We are only focused on delivering our product or service using existing technologies and processes.

Many small and mid-size organizations are in the second group. And likely one or more people have tried using ChatGPT or some other LLM to see what kind of answers it gives, or perhaps what kinds of images it can create.

This is a great starting point, and begins a person’s journey to becoming an AI Evangelist.

As AI continues to transform industries, the role of AI Evangelists has become increasingly important. Effective AI evangelism can drive adoption, foster innovation, and enable your company unlock the full potential of AI.

But, this can be a challenging task, especially where stakeholders may have varying levels of understanding and skepticism about AI. Here are a few best practices to consider:

1. Communicate Complex Concepts Simply

One of the biggest challenges is communicating complex technical concepts to non-technical stakeholders. To overcome this challenge, focus on using simple, clear language that avoids technical jargon.

• Use analogies and metaphors to explain complex AI concepts
• Focus on the business benefits and outcomes of AI adoption
• Use visual aids like diagrams, flowcharts, and infographics to illustrate key concepts

Example: Use ChatGPT to create simple, easy-to-understand explanations of complex AI concepts, such as generating a plain-language summary of a technical topic within your business.

2. Build a Strong Business Case

To drive AI adoption, you need to build a business case that demonstrates the value and ROI of AI investment. This requires:

• Identifying specific business problems or opportunities that AI can address
• Developing a clear understanding of the costs and benefits of AI adoption
• Creating a comprehensive business plan that outlines the implementation roadmap, timelines, and resource requirements

Example: Use Predictive Analytics to forecast the potential ROI of an AI project. For example, if you consider implementing AI-powered chatbots for customer support, you could use predictive analytics to estimate the potential cost savings.

3. Foster a Culture of Experimentation and Innovation

AI adoption requires a culture of experimentation and innovation.

• Encourage experimentation and learning from failures
• Provide resources and support for innovation, such as funding, talent, and infrastructure
• Celebrate successes and recognize individuals and teams that drive innovation

Example: Use LLM platforms to generate and evaluate new ideas. For instance, you could use AI to generate ideas for new products or services, and then evaluate those ideas based on their potential impact and feasibility.

4. Educate and Train Stakeholders

AI education and training are critical to driving adoption and innovation.

• Develop training programs that cater to different levels of understanding and expertise
• Provide resources and support for continuous learning and professional development
• Encourage stakeholders to attend conferences, workshops, and webinars to stay updated on the latest AI trends and developments

5. Lead by Example

Finally, AI evangelism requires leadership by example.

• Demonstrate a deep understanding of AI concepts and their applications
• Share your own experiences and successes with AI adoption
• Encourage others to take ownership of AI initiatives and provide support and guidance as needed

By following these best practices, you can become an effective AI evangelist and drive greater adoption and innovation in your organization.