The SaaS Survivors

There’s no denying the past year has been a bloodbath for SaaS businesses with the MSCI Software & Services World Index down 31% (in USD) vs the broader market. The sentiment has been ‘shoot-first ask questions later’.

Whilst we don’t doubt AI will change the way many of us work, we believe there are software companies well suited to not only survive but thrive in the age of AI. The market has yet to separate the winners from the losers but in this article, we attempt to do just that.

We look at software businesses that have three attributes which we believe leaves them well placed to benefit from AI.

Proprietary Data

Large Language Model’s (LLMs) are only as good as the data the models are trained on. It makes sense then that software built on proprietary data is well positioned to not only repel threats from AI but use AI to provide more value to customers.

Software built on proprietary data is well positioned to not only repel threats from AI but use AI to provide more value to customers

Management teams with attractive data assets aren’t blind to their advantage. They’re not licensing data to LLM providers to be used to build products for others. They are keeping strict control of their data and developing their own AI tools to make their software more valuable.

A good example is Experian, the world’s largest credit bureau. Every time a consumer in the U.S applies for a mortgage, car loan, or credit card there’s a good chance the bank uses Experian’s data and software to help assess credit worthiness. Experian gets paid each time.

Experian holds and manages credit files on 220m consumers in the U.S. and hundreds of millions globally. The data isn’t static and Experian adds 1.1bn new data points each month from 12k individual sources. They have also developed a consumer-facing financial marketplace which has 200m+ members across the U.S, Brazil, and the UK.

Experian holds and manages credit files on 220m consumers in the U.S.

Much of this data is subject to regulatory constraints which creates another barrier to potential competitors. There is no room for AI hallucinations and being right 90% of the time isn’t good enough.

Over the past 20 years management has utilized their data to build software used by banks to assess and analyze lending decisions and help spot fraud. With the help of AI they have helped banks speed up credit decisions – meaning end customers get loans approved faster.

AI might make it easier to build software, but potential competitors can’t provide the same insights and value as Experian without the data.

Experian grew earnings ~8% over the past 12 months and expects earnings to grow 10%+ in 2026 yet the stock is down 33% over the past 12 months on fears it is an AI loser. We remain confident it can continue growing long into the future.

Incumbency

Incumbent providers of mission-critical software are also well-placed to defend against possible new entrants and offer AI solutions themselves. These are the providers of software that run core business processes that companies simply can’t do without.

Incumbent providers of mission-critical software are also well-placed to defend against possible new entrants and offer AI solutions themselves

This means switching providers is rare and is often compared to having open heart surgery whilst continuing to do your day job.

As a result, incumbents benefit from long-term client relationships which can be used as a distribution channel for new products.

SAP is a good example of a business with incumbency, that the market has shot, but we believe is well positioned to benefit from AI. They provide Enterprise Resource Management (ERP) software to the world’s largest businesses. SAP's software is embedded in 99 of the top 100 companies in the world and 77% of the world’s transactions touch a SAP system. It has a retention rate of high 90% and is the backbone of many large enterprises’ IT infrastructure.

SAP's software is embedded in 99 of the top 100 companies in the world and 77% of the world’s transactions touch a SAP system

SAP offers products across business lines including finance & accounting, HR, and supply chain management. By providing software that touches multiple teams across an organization SAP can add business context to what would otherwise be less useful data.

For example, an LLM can identify the product code for a specific piece of inventory but without the business context it doesn’t know where it belongs in a warehouse, or who to invoice when it is sold. SAP’s multiple touch-points mean they can provide this context and therefore make AI more useful.

Under the current CEO the company has increased investment and accelerated the shift to the cloud. He has also moved towards a usage-based, rather than per-seat, revenue model. The changes have seen SAP become more relevant to customers. In 2019 only 9% of customers used 4+ SAP products, today it is 23%.

Major brands like L’Oreal and Nestle are adopting SAP’s new offering and have credited it with improving efficiency.

SAP are in the early stages of incorporating AI into their products, but their embedded software combined with long-term customer relationships leaves them well placed to use AI to continue expanding their relevance.

SAP is looking to grow earnings mid-teens in 2026 and we believe the growth opportunity remains large. Despite solid fundamentals the stock is down 43% over the past year.

Proactive management

Having both proprietary data and incumbency means nothing if management are sitting on their hands. We look for businesses that are run by leaders that are constantly trying to get better and improve their value proposition. AI is no different and we expect those businesses with data and incumbency advantages to lean into AI to improve their offerings and ultimately accelerate growth.

Having both proprietary data and incumbency means nothing if management are sitting on their hands

Both SAP and Experian are doing just that.

In conclusion, while AI will disrupt some software businesses, the market is indiscriminately pricing this risk across the entire sector. This is creating what we believe is an attractive opportunity to invest in companies that have proprietary data, incumbent positions, and management teams that are leaning in and using AI to improve their products.