Bussiness
Selling Is Hard Right Now. Here’s How to Win Business in the Gen AI Era.
Selling is much harder today than it was several years ago. It feels like the software market is shrinking while everyone is scrambling to buy generative AI. What’s changed, and how can you get a leg up?
Based on our conversations with 30 Fortune 500 CIOs and software sellers about their spend and priorities—and our own benchmarking and survey data—we found that, even though the pool of opportunity has contracted, over 85% of winnable IT spend lies outside of the industries most disrupted by gen AI today. The key is knowing where to look for that opportunity and how to win those customers.
In what follows, we’ll parse why selling is so hard today, help you segment the market and identify pockets of winnable opportunity, and then offer advice directly from CIOs about how to close new business in this environment.
Why is it so hard to sell right now?
The entire pie of software spend is just smaller: net-new dollars up for grabs for startups have been cut in half.1 Unless you’re selling cybersecurity or databases whose growth rates have remained strong, your life has gotten a lot harder.2
There are three motivating factors behind this shrinking software spend:
- Macroeconomic uncertainty
- Because of inflation, interest rate uncertainty, and upcoming elections, CIOs don’t have good visibility into the near-term trajectories of their companies. This means they’re unwilling to invest in new and longer-term projects and are scaling back budgets.
- Post-COVID SaaS consolidation
- After the COVID-era software-purchasing frenzy, companies are stuffed to the gills with SaaS. Now, they’re slashing low-ROI software, trying to get more value out of their existing stack, and are much more selective about the new vendors they onboard.
- We’re seeing this play out in the numbers: private enterprise software growth rates were 112% in 2021 and dropped to 60% in 2023.3
- Early innings of gen AI
- There’s an overall mandate to purchase gen AI software, which means that startups are competing with new gen AI-native startups—which, in turn, effectively limits the size of their opportunity even further. Companies are also hesitant to make large investments in any software—gen AI or otherwise—before they understand how the technology landscape will evolve.
Segmenting the market and identifying pockets of opportunity
The good news is that there are still pockets of opportunity for startups, if you know where to look.
Though many might assume that the mandate to buy gen AI means all net-new software spend is earmarked for that purpose, we actually estimate that gen AI products account for less than 20% of net-new software spend in the immediate term. However, based on our research, most net-new dollars are coming from companies considering the impact of gen AI in the future.4 For instance, if a CIO is purchasing a project management solution today, they’ll likely consider if that platform will be disrupted or otherwise automated by gen AI down the road.
In fact, if we segment the software market into three buckets based on when gen AI will most impact customers’ businesses—immediate, medium-term, and long-term—we can see that there’s $3.3T of IT spend (or over 85% of total spend) to win from companies who are either in the medium-term bucket and preparing their businesses for gen AI’s impact over the next 2–3 years (like ecommerce companies) or in the long-term bucket and concerned primarily with ROI (companies that primarily deal in physical goods, like manufacturing firms).
How do I win this new business?
Winning business from companies in the medium- and long-term impact buckets requires a sophisticated selling motion and a solid product roadmap keyed to the actual pain points of companies today: getting ahead of gen AI disruption and showing real ROI.
On the other hand, every founder probably knows what it takes to win business in the immediate-term bucket: offer cutting-edge gen AI solutions that help customers build innovative products. That’s the gen AI selling dogfight we’ve been living in for over a year, and that story should already be familiar to most. That’s not to say that startups can’t still win business from these companies, but rather that their business is a small slice of the pie and the way to win it hasn’t changed.
Below, we’ve taxonomized the characteristics of customers in each temporal bucket to help you understand their pain points, priorities, and KPIs.
We also asked CIOs what they’re looking for and what advice they’d give founders selling into big enterprises today. While they acknowledged that there’s no silver bullet to closing new deals, their advice coalesced around a few key points.
Product-led growth alone won’t hack it
Enterprise sales is back. Be prepared to engage in a heavier sales cycle that will likely include both the CFO and CIO.
Though product-led growth (PLG) can still give you a significant tailwind, you’ll likely need to sell hard and sell high to win new business. The data from public markets companies shows this clearly. PLG companies in the public markets decelerated from nearly 60% y/y in 2021 to 18% in 2023, while top-down companies saw much more sustainable growth rates, decreasing from 30% in 2021 to 24% in 2023. The fundamentals of enterprise sales are more important to get right than ever today: understand how your product fits into your customers’ existing ecosystem and tailor your pitch to their business needs.
Sell on value, not experimentation
The majority of CIOs want software that delivers clear, measurable ROI.
Across the board, companies are looking for tangible value from all their software purchases in the form of cost savings or even revenue. Experimental use cases simply don’t fly for non-gen AI solutions for most companies, and value matters much more than it has for gen AI solutions for these customers. (In fact, a number of companies we’ve spoken with are doubting whether paying for large tech copilots is worthwhile, since the products haven’t been as accurate as they hoped and haven’t introduced any step-function improvements into their workflows.)
That said, there’s a carve-out for companies immediately affected by gen AI, since those products can present an existential threat to their businesses and they have no choice but to buy gen AI products in order to adapt quickly.
Your product roadmap is more important than ever
CIOs want partners to help them understand how gen AI can accelerate their business. The extent to which companies can show 1) how they’re incorporating gen AI on their roadmap or 2) how their product fits into an gen AI-centric world in five years, the better shot they have at winning new business. Again, you don’t need to be a gen AI-native solution to win business, but it’s smart to position your startup as a gen AI or ROI accelerant.
To offer some helpful reference points as you build out your roadmap, these are the most common use cases, service needs, and ROI expectations we’re seeing across buckets. Because customers have such a diverse range of needs and expertise at this moment, we think of these buckets less as discrete tranches and more as a gradient.
- All companies: companies across the board use gen AI for productivity enhancement, including information summary, customer support, and software development, with similar levels of adoption across segments.
- Immediate-term impact: these companies build gen AI into customer-facing applications and work with LLMs directly to build their own internal capabilities, like enhancing data analysis or building a recommendation engine to improve their products. These companies often build their own custom LLM solutions and likely need help implementing and scaling those solutions. Because gen AI could pose a threat to their business, they’re less focused on ROI in the near term for these investments.
- Medium-term impact: there’s more variety in how these companies use LLMs, and these companies also have their eyes on ROI. Some companies may build their own internal tools (e.g. Klarna) while others use third-party applications. The use cases span across productivity enhancing and improving customer-facing experiences (e.g. website chatbot).
- Long-term impact: these companies chiefly use gen AI to deliver measurable ROI and are less concerned with developing an innovation advantage. Some of the early gen AI applications in this bucket fall under sales and marketing use cases, like creating marketing copy or personalizing emails.
There’s also massive opportunity across all buckets at the gen AI app layer, but it’s early. Most of the gen AI software we’re seeing today is the same “app-building”—or infrastructure—software pitched from different angles, likely because we just have gen AI primitives right now. In the long term, however, there’s a big opportunity to displace entrenched enterprise software, both in horizontal applications (like CRMs) and vertical applications (like electronic health records). If you’re building these solutions, consider what you’re doing to win business at the app layer, whether that’s by hand-holding customers through implementation, organizing their data, integrating with other apps, having customers who are familiar with your workflow, or building/nurturing a user community.
Engage channel partners like consultants and large platforms
Given that the impact of gen AI is still uncertain and vendors are consolidating their software stacks, channel partners and large platforms like Accenture have more account control now than before. Consider building relationships with consultants and other channel partners who can include you in the solutions they’re building for their clients, but be cautious about how much ground you cede. Channel partners start to own customer relationships and the implementation of your product, which can impact its perception and use.
Looking ahead
Don’t panic: your read on the current market isn’t off base, and selling is much harder than it was several years ago. That said, for the founders who double down on building sophisticated enterprise sales motions and product roadmaps keyed to customers’ needs as we move into a gen AI-native era, there are still dollars to win. The overlapping cycles of macroeconomic uncertainty, SaaS consolidation, and early gen AI adoption won’t last forever, and the founders who are thoughtful, tenacious, and persistent about finding and winning pockets of opportunity today will stand themselves in good stead for tomorrow—and beyond.
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