It's no news that IT salespeople, like most of us knowledge workers, are increasingly leveraging ChatGPT and other Gen AI tools in their daily work. Sales teams are applying AI to perfect their sales materials and proposals to make their quotas. Lately, their work is being made even easier with the growth of AI-powered RFP response tools.
Companies like responsive.io, vendorful.ai, and proposify.com are offering vendors AI-powered sales-side tools to win more deals with higher-quality proposals and less work. These AI-powered RFP tools enrich AI-generated outputs by drawing on the vendor's existing materials — case studies, past proposals, product documentation — to produce attractive proposals with a tailored, organization-specific touch.
No silver bullet on the vendor side
Despite the rich set of promises, there's of course no silver bullet here. To make the most of these tools — and to differentiate from peers using similar ones — organizations need to have their expertise (credentials, processes, capabilities) well documented.
There's still no substitute for human judgment, the expertise of smart architects, and the passion of hungry salespeople to ensure the entire pitch is accurate, consistent, and convincing.
The same trend on the buyer side
At the same time, a similar AI trend is happening on the client side. Buyers are using generative AI and adopting AI-native tools — such as our Nvelop RFX — that not only help organizations define requirements, generate RFPs, and manage the IT sourcing process, but also support clients in the evaluation and comparison of the proposals. Yes, the same proposals that were partly composed by AI.
While people remain in charge of selecting the right vendors, AI engines are doing a lot of the heavy lifting: analyzing whether proposals meet the requirements, checking compliance with the client's policies, and finally comparing proposals and surfacing the likely winners. The AI tools can even support clients in negotiations and contracting.
Cui bono?
Now, with AI replacing humans on both sides of the table, we are entering an era of IT sourcing where AI is talking to AI. Clients send requirements and RFPs generated by AI to vendors who use AI to create winning proposals, which are again evaluated by the client's AI.
So who's the winner in this machine-to-machine sourcing?
Clients need to spend less time managing laborious IT sourcing processes. They can spend more time discussing their actual needs, optimizing the solution scope, and building internal alignment around their IT initiatives. They are also able to invite more vendors into RFP rounds and can enjoy fact-based, AI-enabled analysis of the strengths and weaknesses of often very extensive proposals.
Vendors will have more time to strategize their winning sales plans and to build real relationships with client stakeholders. They will also be able to answer more RFPs thanks to lower sales costs.
Who loses
The losers will be the vendors who don't have their act together. Like the one vendor I heard was thrown out of a sales meeting when the client realized there was too much A and too little I in their proposal. Relying too much on AI-generated content won't win you the deal.
Vendors who don't have their excellence documented will get little use out of these smart tools. Even AI can't narrate your success stories if you don't let it know.
Likewise, customers with fully manual sourcing workflows can expect to be even more busy in the future. Vendors' AI engines are very good at producing plenty of quality content for clients to review. Good luck digesting all the materials.
What it adds up to
AI-driven IT sourcing will bring real benefits to clients: faster sourcing, accelerated time-to-market, better prices, less time and money spent per project, ensured compliance, smarter decisions.
Vendors will profit as well. A lot of the labor-intensive response work can be automated, and more time spent on thinking about how to bring the most value to the client.
Both sides should be happy. Applying AI is not a zero-sum game.
