How to Identify Business Value and Get Buy-In to Move Generative AI Solutions from PoC to Production
“By 2030, AI is expected to contribute over $15 trillion to the global economy.” That’s not a prediction—it’s a transformation. Generative AI (GenAI) is at the heart of this shift, creating text, images, and even code with astonishing precision. But let’s face it: while launching a proof-of-concept (PoC) for a GenAI project is exciting, moving that solution to production is where the real challenges—and rewards—lie.
Many promising PoCs never make it past the pilot stage. Why? Lack of clear business value, stakeholder buy-in, and a structured deployment plan. Let’s break down exactly how to navigate these challenges and turn your GenAI projects into production-ready assets.
1. Pinpoint the Business Value: Anchor Decisions in Outcomes
A flashy PoC is great, but it means nothing if it doesn’t solve a tangible problem. Start with the basics: What business problem are you solving, and why does it matter?
Zero in on Specific Pain Points
Don’t pitch GenAI as a hammer looking for a nail. Find the nail. Are content production timelines bogging down your marketing team? Is your customer service team drowning in routine queries? Pinpoint areas where automation or efficiency can create measurable results.
For example:
- A retailer used AI to generate personalized product descriptions, slashing time-to-market by 40%.
- A financial services firm deployed AI chatbots, reducing customer response times from hours to minutes.
Attach Numbers to Value
Concrete metrics build credibility. Ask yourself:
- How much time will this save?
- What percentage of costs will it reduce?
- How will it impact customer satisfaction or revenue?
For instance, if GenAI speeds up a process by 30%, tie that to specific dollar savings or team efficiency. Clarity wins support.
2. Get Stakeholders on Board Early: Speak Their Language
No matter how impressive the tech, you need people to champion it. From executives to end users, everyone has a stake in the project’s success.
Identify Decision-Makers and Influencers
Who controls the budget? Who implements the solution? Who uses it daily? Map out your key players:
- Executives: Care about ROI and strategic alignment.
- IT Teams: Focus on scalability, data security, and technical feasibility.
- End Users: Need tools that simplify—not complicate—their work.
Tailor Your Pitch
A one-size-fits-all approach won’t work. Speak to their priorities. For example:
- To executives: “This AI will save us $500,000 annually by reducing manual workflows.”
- To IT: “This solution integrates seamlessly with our current systems, and we’ve accounted for data compliance.”
- To users: “This tool automates repetitive tasks, giving you more time for strategic work.”
Show Results, Not Just Potential
Let your PoC do the heavy lifting. Showcase specific wins, like, “Our initial pilot reduced response times by 35%, handling 60% more queries without additional staff.” Concrete success stories build trust.
3. Tackle Scaling Challenges Head-On
Transitioning from PoC to production is where the rubber meets the road. Issues like data quality, infrastructure, and model reliability can derail even the best ideas.
Ensure Data Readiness
GenAI lives and dies by data. Ask yourself:
- Is our data clean, complete, and representative?
- Are we compliant with privacy laws like GDPR or CCPA?
For instance, if your PoC relied on small, curated datasets, scaling will require broader, real-world data. Build a data pipeline that grows with your project.
Plan for Scalability
A PoC can run on a single server, but production requires robust infrastructure.
- Cloud solutions often offer flexibility, but ensure you’ve budgeted for ongoing costs.
- APIs and integrations must seamlessly connect GenAI to existing workflows.
Test for Real-World Performance
Stress-test your model. Can it handle heavy loads? How does it perform in unpredictable scenarios? Push it to the limits before full deployment.
4. Create a Clear Deployment Roadmap
Moving to production without a plan is like building a skyscraper without a blueprint. A structured roadmap ensures smooth execution.
Phased Rollouts Work Best
Don’t rush an organization-wide launch. Start small:
- Pilot with a single team or department.
- Collect feedback, refine, and scale step-by-step.
For example, a company testing AI-generated content might start with one marketing campaign. Once successful, they can expand to multiple campaigns or regions.
Invest in Training and Change Management
Fear of the unknown can stifle adoption. Empower your teams with:
- Training sessions to demystify the tech.
- Workshops that show how AI complements (not replaces) their roles.
Make it clear: GenAI isn’t here to take jobs—it’s here to amplify human potential.
Monitor and Iterate
Production isn’t the finish line; it’s a new beginning. Establish feedback loops to track performance and refine as needed. Regular updates ensure your AI evolves with your business.
5. Keep Stakeholders Engaged Post-Launch
Success doesn’t sell itself. Keep your stakeholders in the loop to maintain buy-in and momentum.
Report Success with Numbers
Share metrics that matter:
- “The AI tool reduced production time by 25%, saving $300,000 annually.”
- “Customer satisfaction scores increased by 15% after deploying the chatbot.”
Encourage Continuous Innovation
Once you’ve proven success, brainstorm new applications. For example, a chatbot for customer queries might expand to sales assistance or HR support. Build on your wins.
Conclusion: Bridge the Gap Between PoC and Production
Turning GenAI projects into production-ready solutions isn’t easy—but it’s worth it. By anchoring your efforts in clear business value, building early stakeholder buy-in, and planning for scale, you can unlock the transformative potential of this technology.
Remember, the journey from PoC to production isn’t just about deploying AI; it’s about delivering real, measurable impact. Done right, GenAI doesn’t just enhance operations—it reshapes what’s possible. Let’s make it happen!
