It’s an all-too-real scenario for business professionals: getting assigned a high-stakes presentation at the last minute with limited time to understand the topic, craft a proposal, and deliver a high-impact presentation. At Forrester’s Technology & Innovation Forum in Austin last month, we put attendees in this very situation, challenging them to use emerging generative AI (genAI) tools, such as ChatGPT, Google Bard, Pictory, and Adobe Firefly, and experience the promise of this technology.

We presented the participants with the following scenario: A group of local investors were in town looking to fund potential solution(s) for addressing food security in Austin, Texas. The caveat: These civic leaders could only meet in about 90 minutes and expected a full pitch of bold solutions.

With the clock ticking, we directed participants to:

  1. Research the issue. Understand the current state of food insecurity in the city by researching root causes, historic trends, and demographic breakdowns, as well as social and economic costs.
  2. Devise a solution. Develop a commercial or nonprofit idea to address the issue, and build the business plan, including a vision, strategy, funding requirement, forecasted impact, and projected timeline.
  3. Pitch their solution. Create the presentation materials for the venture, including a PowerPoint, promotional video, elevator pitch, and press release.

What We Learned About Using GenAI To Complete Important Work

The energy in the room was electric, a mix of excitement and trepidation, as people from across industries and geographies immersed themselves in an exercise designed to push them outside their comfort zone. Walking around the room, the following became clear:

  • GenAI requires continuous learning. There is no time like the present to create an account for these emerging tools and start feeding them prompts. Even among tech leaders, the familiarity with genAI tools runs the gamut. A few attendees mentioned trying ChatGPT for the first time, while others pushed themselves to test unfamiliar text generation tools like Bing Chat or Claude. Almost everybody seemed apprehensive when it became clear that they needed to use video and image generation tools for the final outputs. One attendee commented, “I hadn’t heard of many video generation tools.” Maintaining one’s expertise in genAI will require ongoing learning as new tools are released and advanced features get added to existing ones.
  • These tools are accelerators. GenAI helps people do more faster. Teams initially worried that our asks were unrealistic given the allotted time, yet within 60 minutes, they accomplished everything we outlined — and some had time to spare. As an attendee commented, “[It was] inspiring to see what we could do in such a short time.” And Glenda Sims, chief information accessibility officer at Deque Systems, observed that “genAI sifted through supporting information at the speed of light.”
  • Human-machine collaboration is key. GenAI tools are new team members, but don’t expect them to do everything or fully replace their human colleagues. Individuals are key to extracting meaningful insights and results from these models. We saw attendees try different prompts and nest questions as they dove deeper into the problem statement. It’s telling that someone commented, “I need to learn best practices for writing prompts.” We also experienced the limitations of genAI that required human intervention to correct. For example, someone shared that they were underwhelmed by the creativeness of image generation tools — the compositions elicited no emotions. Even more troubling were the cases of hallucinations. One team’s press release included an impassioned quote from the mayor of Austin about his city’s challenge with food insecurity. The problem? The quote was made up and attributed to Francis Suarez, the mayor of Miami. Humans play a critical role in getting value from these emerging tools and curtailing adverse consequences.

Sample Solutions For Local Food Insecurity Developed Using GenAI

The teams generated some amazing ideas to address food insecurity in Austin during the hack-a-thon. As an attendee recalled, “In just 50 minutes, we tackled a real-world problem: brainstormed solutions, selected the best one, created a business plan and budget, and crafted a pitch proposal (including authoring a video) with the help of genAI.” Below are just a few of the proposals:

  • Austin Food Bridge. A digital platform that connects people in food deserts with local food, it helps users: 1) find nearby farmers’ markets, community gardens, and food cooperatives easily; 2) access real-time information about available fresh produce and food assistance programs; 3) receive notifications about discounts, promotions, and surplus food from local businesses; and 4) connect with volunteers and neighbors willing to share food and knowledge. Play the promotional video below to learn more!
  • Mobile Grocery Store. This concept is a van that provides fresh, healthy, and affordable food options to neighborhoods without access to grocery stores. View the Gamma App presentation and/or play the promotional video below to learn more!
  • Food On The Go. Offering free meal distribution near designated public transportation routes, this nonprofit packages and delivers excess food from restaurants and other businesses to those in need.

GenAI is a hot topic, and Forrester is here to help you navigate all the potential impacts. We have a dedicated page that highlights our latest insights and offers guidance to help business and technology leaders separate hype from reality — and understand how to get value from generative AI. If you’re a client, schedule time with Rowan Curran, Michele Goetz, or Brandon Purcell, our leading experts on the topic.

If you’d like to hear additional details about our “Hack-A-Thon: Explore The Boundaries Of GenAI” session, please email Elizabeth Cullen ( or Jeremy Vale (