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Will AI bring benefits to the software sector in the second half of 2024?

10 July 2024 - Hardware companies specializing in AI-related products have seen significant growth recently, contrasting with the softer demand and weaker guidance experienced by B2B software firms. This divergence reflects an ongoing cautiousness among enterprises regarding future headcount growth and software license renewals, opting for shorter contracts while awaiting new AI advancements. Despite these prevailing challenges, we contend that firms facilitating specifically structured data flows and effective AI model training are strategically positioned for sustained growth. Looking ahead, while Q2 results may not demonstrate robust performance, we anticipate positive momentum emerging in Q4 and throughout 2025 as AI solutions and market dynamics evolve.

Hardware companies with AI-related products have experienced tremendous growth, while software companies with B2B exposure have encountered softer demand and weaker-than-anticipated guidance. The higher demand for hardware products can be attributed to the market’s investment in infrastructure, akin to buying the gardener’s main tool – the spade. This disparity in performance is evident in the past two years’ ETF data, where the SMH Index (hardware) surged by +130.07%, whereas the XSW Index (software) saw a more modest increase by +27.06%. While the technology market is experiencing a dynamic interplay between hardware and software, we have seen an emerging shift into software. 

The weaker-than-anticipated guidance seen among software companies is primarily a result of the following factors:

  • The AI development: Enterprises are noticing the rapid development in the software market and are waiting for new AI solutions to become available. As a result, we have observed that enterprises are, on average, signing shorter contracts and waiting for new alternatives to emerge during the contract period, being cautious not to invest too much in technologies that may become obsolete quickly.
  • Headcount: Enterprises have also adopted a more cautious approach towards headcount growth and following the number of user licenses needed. Historically, enterprise contracts have often included options to add additional users if the headcount increases. However, we are currently seeing the opposite trend, indicating they expect fewer users by the end of the contract period.
  • Macro: Beyond the above, we are in a softer economic environment and the higher interest rates have led to increased cost consciousness. Additionally, there are several significant macro events on the horizon that could impact the broader economic landscape, leading to a reduced risk appetite. 

Workday, Q1 2024 – Carl Eschenbach, CEO & Director: “And we are seeing customers committing to lower headcount levels on renewals compared to what we had expected. We expect these dynamics to persist in the near term, which is reflected in our revised FY 2025 subscription revenue guidance.”

Salesforce, Q1 2024 – Brian Millham, President & COO: “We continue to see the measured buying behavior similar to what we experienced over the past two years and with the exception of Q4 where we saw stronger bookings. The momentum we saw in Q4 moderated in Q1 and we saw elongated deal cycles, deal compression and high levels of budget scrutiny.”

Whether individually or collectively, these factors are constraining enterprises from increasing their spending pace, resulting in weaker billings that have negatively impacted many software stocks.

Weaker billing – a problem or not?
We question whether weaker billing is indeed a problem, as this remains to be demonstrated. While weaker billing is seen as a higher risk that could lead to churn, it is not necessarily an absolute issue. It is crucial to recognize that enterprises face substantial switching costs when transitioning software solutions, involving significant expenses and time investment. Additionally, the hesitation of enterprises to invest in new (AI) technologies, fearing that these products may become outdated quickly, is a factor to consider.

Will a higher average sales price offset less users?
As enterprises take a cautious approach towards future headcounts, we aim to look beyond companies with pricing models based solely on the number of users. Instead, we focus on those incorporating a consumption-based pricing component. Additionally, we distance ourselves from companies that we believe will not be able to develop an AI solution capable of commanding a higher average sales price (ASP) to offset fewer users. We believe that companies offering leading AI solutions can gain market share from those that cannot and achieve a higher ASP for their products, thereby compensating for lower sales volumes.

Why is highly normalized and federated data important? 
What we know is that AI solutions require substantial amounts of data, which underscores its growing importance. Another crucial aspect is the need for highly normalized and federated data to train AI models effectively. The more well-structured the data is, the better AI can be deployed for generative purposes. Much like hardware, structured data for AI model training serves as infrastructure in the AI space – essentially another piece of equipment during the ‘gold rush’.

Therefore, we believe that companies specializing in data observability and data structuring are in a favorable position. In the first quarter, we observed an increase in current remaining performance obligations (cRPO) for companies like Snowflake and Datadog, indicating that enterprises are actively reserving capacity with them.

In addition, cloud companies like Amazon (AWS), Alphabet (Google Cloud) and Microsoft (Microsoft Cloud) are benefiting from the same trend, and we started to see an accelerated revenue growth among their cloud solutions in Q1.

Key metricAmazon Web ServicesMicrosoft CloudGoogle Cloud
Q1 2024 Revenue ($ bn)25.0426.709.57
Y/Y growth17,2%20,9%28,4%
Operating margin37,6%Not disclosedNot disclosed

Concluding remarks
Building AI capabilities is indeed costly, and to date, we have not seen substantial top-line or profit impacts from AI solutions within the software sector. However, we anticipate that this will change over time, and we believe that companies developing the leading AI solutions will capture market share as the technology matures and its benefits become more evident. 

Two categories of theme leaders: 

  • Returning to the core, building powerful AI solutions requires substantial data and significant capital investments, making it primarily feasible for market-leading companies. We believe that companies offering leading AI solutions can gain market share from those that cannot, achieving a higher average sales price (ASP) for their products and thereby compensating for lower sales volumes.
  • Solutions that lay the foundation for structured data flows and enable effective training for AI models include those offered by Alphabet, Amazon, Datadog, Microsoft, and Snowflake, among others.

From a timing perspective, we do not anticipate strong Q2 2024 results from the software companies. However, we anticipate seeing more positive data points in Q4 2024 and throughout 2025.

For enquiries, please contact: Inge Heydorn, Partner, at and Ofelia Aspemyr, Associate, at

About GP Bullhound: GP Bullhound is a leading technology advisory and investment firm, providing transaction advice and capital to the world’s best entrepreneurs and founders. Founded in 1999 in London and Menlo Park, the firm today has 12 offices spanning Europe, the US and Asia. For more information, visit

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