Traditional technology selection practices fall short for adopting today’s AI productivity tools. Rather than relying on top-down decisions, we’ve embraced a system of structured flexibility and experimentation.
Is your organization stuck in decision paralysis over AI tools or frustrated with your current toolchain? Here’s how a flexible approach unlocked progress for us—and how it might help you.
Structured Flexibility and Experimentation
Here’s how our flexible approach to adopting AI tools worked:
- Focus on needs, not specific solutions:
Our goal is to embrace AI tools responsibly to create more value for our customers. - Set clear guardrails:
- Don’t use tools that use our inputs to train.
- Ensure we understand all the code we commit.
- Never use proprietary customer data in AI tools unless that’s the point of a customer-specific AI project.
- Highlight insights from internal champions and super adopters:
Encourage presentations at company meetings and assign key roles on project teams. - Open communication channels for continuous learning:
Slack has been a valuable platform for sharing experiences and tips. - Centralize licenses and acquisitions with IT:
This helps align tool usage with guardrails, track performance, and avoid long-term lock-ins by steering clear of multi-year agreements.
This system allowed us to act quickly, remain adaptable, and continuously learn as AI tools evolved.
Traditional Methods vs. Our Approach
Why does flexibility matter? Traditional methods, while effective in stable environments, falter with fast-evolving AI tools. Here’s why:
Traditional Process:
- Identify three to five solutions based on business needs.
- Engage stakeholders and narrow the list to two or three options.
- Pilot the top options.
- Make a final decision based on cost and functionality.
This approach often takes months to complete. Once a decision is made, organizations tend to stick with the chosen tools for years, even if better options emerge.
Our Approach:
Instead of a prolonged evaluation, we prioritize experimentation and adaptability. We focus on building expertise and iterating with tools that fit our current needs, knowing that rapid evolution will demand ongoing adjustments.
Why Flexibility Matters: Two Key Factors
Adopting AI tools stresses traditional processes because of two key factors:
1. Early Adopter Advantage
Organizations that adopt early gain a competitive edge through efficiency and productivity. Those who lag risk falling behind and struggling to remain competitive. As I discussed in my post Generative AI Adoption is Competitive Table Stakes – Don’t Get Left Behind, this shift is essential to staying ahead in the market.
2. Rapid Pace of Change
Since ChatGPT’s launch in November 2022, new AI productivity tools have emerged at an unprecedented pace. Significant investments in AI, as highlighted in WSJ’s article The AI Spending Spree, in Charts, suggest this rapid evolution will continue for years.
How We Found a Better Way Forward
My partner Mike and I felt the urgency of being early adopters. Staying competitive through quality and productivity drives us, but we couldn’t confidently prescribe a perfect set of tools or processes.
We arrived at a more flexible approach because:
- We believed in acting without certainty: Waiting for a perfect solution felt riskier than experimenting with imperfect tools.
- This wasn’t just about efficiency: AI represents a fundamental shift, not a simple system replacement.
- We saw long-term value in early expertise: Building expertise early positions us for ongoing success, even as tools evolve.
Mike provides an overview of our experience during this part of a panel discussion about the impact and application of artificial intelligence.
Reflections on Our Approach
Looking back, I’m grateful we embraced flexibility in AI tool adoption. The ecosystem evolved faster than we anticipated, and our team’s experimentation and innovation exceeded expectations.
If your organization is stuck evaluating AI productivity tools, consider shifting from a centralized decision-making model to a structured, flexible approach. It may feel uncomfortable at first, but it can unlock progress and position your team to thrive in an ever-changing landscape.