Fairmarkit Projects GenAI Will Reduce Intake-to-Source Cycle Times by 95%+ and Dramatically Increase Procurement’s NPS

Going Beyond the Checkbox: Our Early Journey with GenAI

Back in March, our customer BT Sourced invited me to speak on a panel about generative AI. Artificial intelligence has been a core pillar of our platform for over 4 years, so I walked in feeling confident I could add value to the conversation. Overall it was a great discussion, but after the session, it was clear just how much more there was to learn.

With GenAI progressing at warp speed, it can feel impossible to keep up with all the new developments. 

Entire fields and business landscapes are on the precipice of a full-blown AI transformation. Our Execs and I knew the time was right to go all-in and embrace our GenAI journey. With the sheer number and size of early-stage bets being made, one thing is clear: there will be many big winners and even more wild misses. Only time will tell. 

Heaps of companies have shifted their messaging to center AI, and it’s tricky to weed through all the bandwagoners to find truly important solutions. I was speaking to another founder and CEO who has successfully used AI for the past 4-5 years and something he said stuck with me. “AI isn’t binary. Just because you say you have it doesn’t mean it’s impactful, powerful, or solving a real business problem.” Without a real value-add that provides a competitive advantage, AI is only a short-term checkbox. To take the checkbox comment a step further with an analogy, say two people can both “communicate” so they hit a “can you communicate” checkbox. But one is via video conferencing, and another is through messenger pigeon. There's a massive difference in the speed, quality and density of information exchanged. Not to mention the user experience.

So the question we’ve been asking ourselves at Fairmarkit: if we’re going to take GenAI to the point of real value, how do we stay up to date and start experimenting?

Step 1: Learn everything there is to know. 

Easier said than done, since it’s changing incredibly fast. Even if you’re educating yourself on a weekly basis, you’re still probably behind. It’s like trying to hit a moving target. Challenging, but also inspiring. 

The resources we encountered were dense and tough to get through–-50-page publications and university lectures. I’ll say, some of the one-off videos were real hidden gems.

One really hit home as it was showing examples of the pace of change across different iterations of launches. An older version of the GenAI platform was instructed to create a picture of a unicorn. The result was terrible and looked like my daughter drew it. Our 1-year-old, not our 2-year-old. The newer version’s work could have been done by an adult with “OK” drawing ability (not yet a professional artist, but it’ll get there fast). The difference between different iterations of generative AI that was being released months apart was staggering, as GenAI was truly starting to understand more complex concepts and return more creative and unique responses (insert head exploding emoji here).

Step 2: Trial and error.

We set up an internal GenAI SWAT Team, and the first thing we did was set up a GenAI platform for our internal IT support via Slack. Not perfect, but a hit. Then we decided to enable our help portal with GenAI, so customers wouldn’t have to dig through a massive pile of documentation to find answers. Once again, not perfect, but a hit. 

It was then time to get our customers involved in the design process. I called a handful of customers with this message: “We don’t know what we’re building, what the time commitment will be, or even a ballpark on an estimated timeline. We do know GenAI isn’t a bubble and we’re looking to partner with our customers to get educated together on this journey. Our thought is if we don’t dive in head first now, in 6 months we’ll already be too far behind to catch up.  Want to join?” Zero hesitation from everyone I called. We kicked off our Friday brainstorming sessions that week.

We committed to launching new versions of whatever alpha we built every week, adopting an agile and scrappy approach to deploying. It was also key to keep an open mind on where we’d go. We considered where we had proprietary access to data, how we could move the needle for our customers while opening up new markets, and where we already had a strong foundation, among other points.

During the next month, we pulled in more customers from outside our target demographic, met with GenAI teams from our VCs, networked with other AI leaders, and continued to hone our beta until it was ready to demo. Taking a true startup approach, everyone was doing work in between their normal load of managing their teams and projects, jamming on the weekends, and working super late nights, with the ultimate goal to build something truly exceptional.  

By May, we made a commitment to have the beta ready for customers and the company to use by the end of the month. The team hit that timeline. We launched for company use, received 50+ pieces of feedback and improvements, and rolled it out to 10 customers soon after (with a 100% acceptance rate). That led to another 50+ pieces of feedback which then turned into dozens of zooms and in-person GenAI workshops with our customers. With continuous updates to the beta every week, we’re continuing to refine the scope and targeting a full release in the next 1-2 months. Disclaimer: as new developments come out, that timeline may change. Working to beat the clock is half the fun.

Step 3: Moving Forward

Along with sharing our GenAI journey, this is all a very roundabout way of informally announcing that our GenAI beta will be launching in the near-future. From working with early beta customers, we project that it will dramatically improve procurement’s NPS, enable procurement to significantly increase savings by sourcing X% more events (not trying to dodge a “%”, just want better confidence on the number prior to making a claim), and also decrease intake-to-source timelines by upwards of 95%+. 

Once it’s ready I’ll write another post covering our thought process around how it fits into our product roadmap, where we’ll be taking it next, and how it will enable greater collaboration and sourcing at scale within our platform (which Gartner has kindly dubbed best-in-market).   

That’s it for now, and I hope this quick overview encourages more teams to start and/or accelerate your GenAI journeys. Creating an open space to have creative workshops and dialogue inspires a companywide art-of-the-possible mentality, which is what typically leads to some truly disruptive tech.  To quote my co-founder quoting JFK, “A rising tide lifts all the boats.”