AI vendors report that they’re facing many challenges in selling AI to enterprises in USA and other markets. According to the Economic Times article entitled Scoring with AI not Enough to Crack US Enterprise Code, they’re learning that merely having an AI solution is not enough.
Surprise surprise said no one!
The cardinal principle in a capitalism is that product / manufacturing is tablestakes, and differentiation comes out of marketing, so having an AI solution is certainly not enough.
In this blog post, we’ll outline the top five challenges faced by AI vendors and provide our guidance to overcome them.
Challenge #1: In the last couple of years, AI has changed the landscape by drastically bringing down the time taken to develop a product. This has resulted in proliferation of AI platforms and applications, cluttering the market, increasing competition and changing the enterprise sales dynamics.
How We Can Help: By making it easier and faster to develop software than normal free markets, AI has taken the above cardinal principle of capitalism to the next level. To that extent, it has propelled the importance of marketing to a higher orbit.
We help AI vendors to differentiate themselves by packaging their product features and service capabilities into compelling reasons to buy that rhyme with business pain areas and resonate with industry hot topics. Our Marketable Items enable AI product and services vendors to stand out in the cluttered market. Please find a few examples of Marketable Item in the following exhibit.
Challenge #2: Enterprises are often seeing over 20 vendors that are selling similar products and hardly have time for demos with each of these firms.
How We Can Help: Traditional GTM motions around features, benefits and thought leadership have stopped working in crowded markets. And, with 20 vendors in a single product category, Enterprise AI is surely a very crowded market.
We use Marketable Items to convey your value proposition more compellingly than other vendors and thereby help you to stand out against your competition. Even if prospects see only three demos from 20 vendors, they’ll want yours to be one of them.
Talking of demos, we had a quick glance at the websites of many AI solution providers. Fewer than half of them have an explainer video. We strongly recommend vendors to create a 2-minute explainer video.
In the past, it was quite cumbersome to create explainer videos. But gen AI has changed that. You can use AI video makers to create the first cut of an explainer video in minutes. In GenAI Satisfies My Craving For Explainer Video, we describe how we used a popular genAI video website to create such a video for our company.
Challenge #3: Enterprises are unsure of ROI of AI.
How We Can Help: AI is a discretionary purchase. Enterprises have been running without AI in the past. They can’t be faulted for thinking that they can run without AI in the future. The Gartners, McKinseys and Sam Altmans may claim they’re wrong but most CIOs and CFOs know how to tune out hype, and will buy AI only if they see business value in it.
This is not something new with AI. Unlike consumer technology, enterprise technology adoption has always required vendors to convey business value. Even 40 years ago, to sell a 40K PC, I’d to list the business benefits to the owner of the company and offer to connect him to reference customers who already were getting those benefits after buying our PCs. Ditto ERP 30 years ago.
As mentioned earlier, marketable items can help in this pursuit. Beyond that, explainer videos described above might suffice to seal smaller deals. For larger deals, though, vendors might need to carry out scripted demos aka Proof of Concepts using prospect company data. We can help in this regard by spec’cing the scope of PoCs vis-a-vis data sources, feature sets, and areas of ROI.
Hey ChatGPT: Can you scour the archives of El Reg and get data about any technology in the history of humankind that delivered ROI to 5% of its customers within 3 years of its launch? https://t.co/iEkh9qoHuR via @theregister
— SKR (@s_ketharaman) August 19, 2025
Challenge #4: Data quality concerns are hampering enterprise AI offtake.
How We Can Help: AI is trained on data, therefore data governance will inevitably play a paramount role in the adoption of AI by companies. This is even more true in the case of Agentic AI, which takes actions autonomously.
However, we believe that vendors and customers are missing an important point: Previous technologies demanded pristine data quality without themselves playing any part in improving the quality of data whereas AI provides tools to do that.
When I predicted that AI will make GIGO obsolete in Ten Revolutionary Things About AI – Part 1, very few people took me seriously. However AI practitioners are now increasingly seeing the potential of using AI to improve data quality. CIO exhorts companies to Use AI to improve data. Martech goes one step further:
LLMs may take garbage in and get gold out.
It’s almost like AI has changed the full form of GIGO to Garbage In Gold Out!
Challenge #5: Earlier it would take 6-9 months to get a signal from a prospect as to whether they are interested in the product or not. Now that is taking 12-18 months. Overall, it’s taking longer to run pilots and conclude deals.
How We Can Help: By positioning your products and services as solution for business pain areas, we help you to gain access to LOB leaders at your prospective customers. This will enable you to showcase your offerings and convey your value proposition directly to the folks who control budgets. With this newfound capability, you’d be able to start pilots earlier and accelerate the sales cycle so that you can close deals faster.
Please reeach out to us if you need any help in selling your AI products and services to enterprises in USA and other markets.