Aspirational Selling is selling to aspirational goals of the customer, with a proven track record of achieving those goals for other customers in the past, and every intention of achieving them for the said customer at present. – Aspirational Selling Is Not Overselling
In our GTM work around Enterprise AI with nearly 100 prospects and customers, we have observed three major trends:
- Overestimation of ability to change
- Renegotiations
- Alternative pricing models
I forsee that they will take aspirational selling, which is already a common practice in the software industry, to another level in Enterprise AI sales.
1. Overestimation of ability to change
Enterprises overestimate their ability to change.
This is a chronic issue in Enterprise IT. Before the implementation of any large and complex enterprise software begins, companies believe they can do whatever it takes to succeed. But, after the implementation begins, there are sudden references to cybersecurity, legal, compliance, and other bogeys. Their ability to change wanes with time.
Account managers need to manage expectations. But expectation management is an art. If a vendor highlights change management challenges during pre-sales, customers may rush to brand it as pessimistic and / or conclude that it’s not capable of making things happen, and remove it from their shortlist.
While AI demands greater need for enterprises to change, the hype around AI boosts enterprises’ confidence in their ability to change.
So, aspirational selling, which has been a practice du jour in Enterprise IT sales for all technologies, might scale new heights in Enterprise AI.
“Underpromise and Overdeliver” worked in 20th century. In 21st century, success mantra has changed to “Overpromise and Overdeliver”. Anyone who underpromises will get wiped out without even getting the chance to showcase their delivery capabilities.https://t.co/c63j8CpWyC
— SKR (@s_ketharaman) May 4, 2022
2. Renegotiations
There are re-negotiations.
Renegotiations in AI deals may go beyond cost and timelines and include success criteria.
To this extent, AI will echo ERP.
Per survey conducted in 2020, the percentage of companies that rated their ERP project a success went up from 58% in 2015 to 58% in 2019. The key reason for the sharp increase was “To avoid reputational damage coming from failure, customers redefine success as whatever they get.” Not because there was a significant increase in the ability to change or improvement in expectation management.
3. Alternative pricing models
AI-based contracts are abuzz with alternative pricing models.
IT Services companies have traditionally followed time-and-material and fixed price engagement models.
There’s a lot of talk about outcome-based pricing in AI deals.
But it is not such a paradigm shift as it’s made out to be in the popular narrative.
IT Services companies have attempted outcome-based pricing in the past. The challenge is, at early stages, customers expect vendors to take on risk with uncertain returns, which leads to severe margin pressure; whereas, at later stages, customers balk at paying vendors a percentage of cost saved or revenue gained, want predictable billing, and demand a return to fixed price, so vendors can’t fully encash the upside.
Therefore, outcome-based pricing never worked at scale in the IT Services industry.
To cite an example from our firsthand experience, an LMS vendor quoted a fixed price for its software. Prospects demanded outcome-based pricing. We crafted a new marketable item around outcomes that elevated the product’s appeal and ticket size to a new level.
But you’d be wrong in thinking that everything was gung-ho after that.
The same customer that demanded outcome-based pricing model before shuddered at having to part with a percentage of reduced costs after a year, and insisted on returning to the fixed pricing model. We agreed but we also switched from guaranteed benefits to contingent benefits.
We’ve already started seeing early signs of this in Enterprise AI. Microsoft and Anthropic recently switched from seat-based to usage-based pricing. Many customers are displeased. Some are trying to switch to other LLM providers.
Banks should be jumping with joy when Anthropic recently changed its pricing from per-seat to usage-based. But they’re doing the opposite – reconsidering their use of Anthropic. If Anthropic shifts to outcome-based pricing, I can bet that customers will totally dump Anthropic.
— SKR (@s_ketharaman) April 24, 2026
Then there are many output-based pricing deals packaged as outcome-based pricing deals, as I highlighted in my blog post entitled Outcome Washing In AI Deals.
Aspirational Selling is not misselling.
Due to internal constraints, not every customer can implement every feature supported in ERP, CRM and other enterprise software. But it’s not overpromising for sales to talk about them – as long as they’ve been implemented by some other customer. https://t.co/c63j8CpWyC
— SKR (@s_ketharaman) April 7, 2023
