Thematic investing focus: Cloud-backed AI and enterprise intelligence

Jeff Wantman, Global Industry Analyst
Aaron Koh, Investment Strategy Analyst
2024-06-30
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The views expressed are those of the authors at the time of writing. Other teams may hold different views and make different investment decisions. The value of your investment may become worth more or less than at the time of original investment. While any third-party data used is considered reliable, its accuracy is not guaranteed. For professional, institutional, or accredited investors only.

A variety of secular trends are spurring innovation and disruption in the global economy and creating what we believe are attractive thematic investment opportunities. In this series of articles, we take a close look at some of these trends, the breadth of the opportunity set and the related risks. 

In this article, we focus on enterprise intelligence — a set of technologies that enable companies to analyse and leverage data in pursuit of better business decisions. Specifically, we look at how cloud-based computing and artificial intelligence are transforming the way enterprises operate, creating what we believe will be a secular tailwind for companies providing software, machine learning tools and cybersecurity. 

Among our key conclusions: 

  • The migration to a cloud-based model is driving productivity gains and still has more runway ahead. 
  • Large-scale migration to the cloud is laying the groundwork for companies to exploit artificial intelligence and machine learning, as access to large datasets helps the development of sophisticated AI programs. 
  • Rising wages and skilled worker shortages will accelerate the adoption of AI as companies seek to reduce labour costs, increase productivity and optimise the performance of their products and services.
  • Multiple points of access and increased digitalisation also mean that companies will need to invest heavily in cybersecurity to avoid reputational and financial risk.

A crash course on enterprise intelligence trends

Cloud computing gathers pace – A new era in digital infrastructure has emerged, offering opportunities for software providers, and driving demand from their enterprise customers. As companies seek to increase productivity and take advantage of technological advancements, software spend has steadily increased.1

Much of that spend is directed to cloud computing, which is transforming the way enterprises access software services, with traditional, on-premises solutions giving way to a new model. 

Companies have shifted to the cloud because of its potential for greater flexibility, lower costs and better functionality. Traditional on-premises solutions required companies to pay large up-front costs for perpetual software licenses and then commit to the infrastructure, hardware and IT resources to accommodate, run and service these programs over the long term. In contrast, cloud-based software providers are more likely to assume an as-a-service model, whereby customers pay monthly subscriptions, and providers are incentivised to continuously improve functionality, enhance services and remain engaged with customers. This creates opportunities for software companies to translate these increased touch points to higher lifetime value and higher-quality revenue streams. 

There remains a long runway for full migration of software services to the cloud. In 2018, 74% of workload spending was on-site, but that figure is expected to decline to 35% by the end of this year.1 Industries such as manufacturing and construction have been slower to migrate, but we believe software spending will continue to grow in the pursuit of greater productivity and that the pace will pick up in areas that have been slower to make the shift to cloud. 

Case in point: A cloud-based IT services company automating business processes

The cloud and automation are already intersecting in the technology sector. One example is a cloud-based IT services company, which streamlines and automates business processes (for example, IT service requests) to enhance enterprise efficiency and lower the cost of critical support services.

This example is for illustrative purposes only and not intended as an investment recommendation. 

Machine learning is becoming more sophisticated – As the migration to the cloud runs its course, another opportunity arises from its potential to help drive significant advances in machine learning and artificial intelligence (for example, large language models or LLMs, as well as tools for media and code generation). Software has already displaced some routine occupations, but AI has the power to disrupt higher paid roles (Figure 1). Cloud data, along with recent breakout technologies, will make it easier to conduct machine learning over multiple datasets and create AI programs that can handle non-routine roles. Where direct replacement does not occur, AI “co-pilots” that augment workers should help boost productivity, while machine-learning technologies could supercharge enterprise automation activities.

Figure 1
ldi-alert-keep-your-spread-fig1

With CEOs citing rising wages and labour shortages as their most pressing concerns,2 and an ongoing need to drive productivity gains (made more urgent in countries with rapidly aging populations), we expect companies to invest in AI in a bid to improve business outcomes and reduce costs. 

While productivity gains should help pay for these tools, we expect that over the mid to longer term, some of this budget will likely come from headcount, similarly to how budget for new IaaS/SaaS platforms came from budget previously used for hardware and software licenses. A normal trajectory of headcount growth typically sees companies spend an additional 1.5% – 2% each year on salaries. Even if a quarter of these additions were displaced by intelligent software, we estimate companies could save US$300 billion of incremental spend in the US alone — versus a total software market of around US$700 billion today.3

This will benefit not only providers of AI, but also its enablers — software companies involved in increasing computational power, storing and managing data, and enhancing connectivity.

Cybersecurity risks are proliferating – With more points of access and increased digitalisation across enterprises, cybersecurity risks have become increasingly prevalent. According to Cisco, distributed denial-of-service (DDoS) attacks — which target networks — were on pace to increase twofold from 2018 to 2023. But not only are we seeing an increase in the number of attacks, the scale and economic impact of these is also growing.

The evolving nature of cybersecurity attacks and their potential to damage credibility while incurring high costs will make investments into cybersecurity an ongoing, and increasing, imperative. This creates an opportunity for cybersecurity providers to emerge as leaders in the field. This is another area where AI can be a useful tool, helping with network security, threat detection, data protection, analytics and identity services. However, AI will inevitably also introduce new risks and usher in a new paradigm for enterprise cybersecurity.

Case in point: An innovative cybersecurity company 

As digitalisation evolves and grows, cyber threats transform with it, and companies helping safeguard digital infrastructure become critical. An example is a cybersecurity company that is leading innovation in advanced security solutions, including next generation firewalls, threat intelligence and endpoint protection to protect against cyberattacks.

This example is for illustrative purposes only and not intended as an investment recommendation. 

The investment opportunities and risks

We believe these trends will benefit a variety of companies within the software sector, including:

  • Companies offering a range of cloud-based and AI software solutions across productivity, resource planning, digital media and marketing, data analytics and video connectivity
  • Providers specialising in industry-specific cloud-based solutions for sectors that are slower to digitalise and migrate to the cloud
  • Companies that are enabling advancements in AI, such as those that support machine learning or that support data storage and retrieval, including data management platforms
  • Providers of cybersecurity software

As with any investment theme, there are risks to our outlook. We see cybersecurity as an opportunity but also a risk. Cyberattacks will evolve, becoming more sophisticated and more common, and companies will need to invest heavily to protect themselves from growing reputational and financial risk. The outlook for this theme could also be impacted by ESG-related risks, such as cloud computing’s energy consumption and storage locations, as well as the impact on labour and society from the displacement and replacement of people by powerful software tools. In addition, with the democratisation of AI capabilities, the risk from bad actors and disinformation rises. With that provision, we believe there is a significant opportunity for active investors within the theme of enterprise intelligence to identify long-term beneficiaries from this secular tailwind in areas such as cloud-related software, machine learning and cybersecurity.

Dive deeper into Wellington’s recent research on AI.


1Gartner, Wellington Management. | 2Duke CFO Survey/Federal Reserve Bank of Richmond. | 3Gartner, 2022.

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