The 4 Biggest Trends Shaping the Technology Sector

11 Jun 2024 The 4 Biggest Trends Shaping the Technology Sector

Authored by RSM US LLP, June 11, 2024

Technology companies are adapting as macroeconomic conditions shift and the hype around artificial intelligence continues. In this environment, a handful of trends are shaping how tech businesses prioritize, grow and focus their operations.

Here are the top four trends RSM has identified for the industry:

1. Scaling and capital markets

For growing technology companies, there is no straight route to scaling up. Each stage of growth brings significant opportunities, along with challenges and numerous ways to tackle them. The intense competition for talent, the constant need for innovation and the make-or-break demands of managing capital affect all businesses in the tech space, but for those focused on scaling up and unleashing growth, intentionality in addressing those challenges is paramount.

Tech businesses need to assess various avenues for sustainable scaling, including build-versus-buy strategies, capital markets and windows for initial public offerings, management of cash burn while driving growth, and strategic partnerships. A thorough assessment can better prepare the business for investment and ease navigation of the fundraising process.

In the current interest rate environment, capital efficiency is crucial. When it comes to investment decisions, technology businesses need to strike a balance between risk and innovation and understand how to foster innovation amid leaner operations.

Learn more about key considerations at each stage of the business cycle

2. Cybersecurity and data privacy

Cybersecurity is imperative for any business, but especially for technology companies, which provide the foundational infrastructure for most aspects of our lives. New rules from regulators are putting even more focus on cybersecurity.

The U.S. Securities and Exchange Commission in July 2023 released final cybersecurity rules requiring public companies to disclose details on material cyber incidents and information on their cybersecurity risk management, strategy and governance. The rules signal a pivotal evolution in the regulatory landscape. Compliance requires proactive measures, strategic planning, a holistic approach to safeguarding data and operations, and a shift from an approach emphasizing regulatory environments to a focus on protecting the broader enterprise.

Further regulation is likely, as the Department of Homeland Security is expected to adopt a new rule for critical infrastructure segments, including telecommunications. The proposed rule will require every owner and operator in key sectors to report a cybersecurity incident within 72 hours and a ransomware payment within 24 hours.

While many larger public organizations likely already have processes and resources in place to meet these requirements, emerging and middle market public companies may need to make structural and cultural changes to enhance or adopt cybersecurity oversight, management, and reporting processes to comply with the final rules. Technology companies must prioritize robust cybersecurity and data privacy measures to build and maintain consumer and investor confidence. Accelerating the transition to cloud computing could be a strategic move to enhance overall cybersecurity.

In addition to complying with new cybersecurity rules, companies must continue to adapt to updates from regulators on other topics, such as corporate sustainability reporting. The final climate-related disclosures rule adopted by the SEC in March 2024 presents public companies with an array of challenges centered on balancing the need for comprehensive reporting with the desire for simplicity and efficiency.

3. Global expansion

The normalization of remote work in recent years has brought new global expansion possibilities for many technology companies. Those that decide to broaden their operations or workforce to new locales or countries need to do so strategically and with careful consideration of international regulations and technological scalability, among other factors.

On the regulatory front, companies need to understand foreign in-country tax and audit considerations, labor and employment laws, and intellectual property use issues that might accompany global expansion. Pros and cons are likely to arise in numerous areas; when it comes to the workforce, for instance, expansion opens access to a broader talent pool but also involves a variety of cultural considerations and different competition for that talent.

Across the broader economy, the labor market is cooling but will remain tight by historical standards for the foreseeable future, according to the RSM US Middle Market Business Index January special report on workforce. The employment figures in the tech sector show that layoffs continue, according to Crunchbase. At least 49,750 U.S. tech sector employees were laid off in 2024 as of May 10. We anticipate this means 2024 will be on par with 2023, when nearly 200,000 tech employees were laid off.

4. Artificial intelligence

The acceptance of AI-related tools has accelerated significantly, driven by the emergence of chatbot programs with advanced language processing capabilities. The middle market stands to gain both directly and indirectly from natural language advancements as the barriers to entry are lowered and the middle market workforce can extract more value from technology tools and systems already in use.

Technology companies can tap into AI-powered data analytics to improve business and customer insights and drive a more tailored experience for users. At the same time, leadership teams need to develop guidelines for ethical AI governance and drawbacks related to AI. As this technology proliferates across industries, malicious actors are using it to refine their methods of carrying out cyberattacks. Tech companies should bolster employee training, prepare an incident response plan and even consider increasing their cyber insurance.

Companies also need to understand the energy implications of growing AI use, including power grid capacity. AI systems, especially those that use advanced machine learning models, require extensive computational resources, including high-powered processors.

The energy needed for annual training of a large language model—a type of AI—is equivalent to that of 130 U.S. households, according to the International Energy Agency. The IEA estimates that if LLMs were integrated into the roughly 9 billion web searches performed daily, the annual energy consumption would be equivalent to the energy usage of approximately 1.5 million European Union residents.

Tech companies will need to work with the energy sector and be creative to maximize efficiency and not overpower the grid.

This article was written by Andrew Fedele, Justin Krieger and originally appeared on 2024-06-11. Reprinted with permission from RSM US LLP.
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