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AI Is Forcing a New Reality Across the Software Industry

The tone surrounding the global software industry has shifted dramatically as artificial intelligence reshapes the competitive landscape. According to David Chen, Morgan Stanley’s head of global technology investment banking, the sector is no longer operating in a period of steady growth and incremental innovation.

Instead, Chen says the industry has entered a far more intense phase where companies must rapidly adapt their products and strategies to survive the AI transformation.

Speaking after the annual Morgan Stanley Technology, Media and Telecom conference, Chen described the current environment as a “battle phase” for software companies. Firms that successfully integrate artificial intelligence into their core offerings could see enormous growth, while those that fail to adapt risk losing relevance.

The conference brought together some of the most influential figures in the technology sector, including AI leaders and CEOs from major enterprise software companies. Executives such as OpenAI’s Sam Altman, Anthropic’s Dario Amodei, Nvidia CEO Jensen Huang and Microsoft CEO Satya Nadella appeared alongside dozens of other tech leaders trying to reassure investors that their businesses are prepared for the AI revolution.

Investor Questions Have Shifted Dramatically

One of the biggest differences compared with last year’s conference was the type of questions investors were asking.

In 2025, many companies focused their AI strategies on improving efficiency. Businesses spoke about using AI-powered tools, copilots, and automation to reduce costs and increase productivity. In many cases, the benefits were framed as modest improvements to operating margins.

But Chen said that conversation has changed completely.

Investors today are far less interested in hearing about incremental efficiency gains. Instead, they want to know whether a company will ultimately benefit from AI or be disrupted by it.

The key question investors are asking is simple: does artificial intelligence strengthen a company’s long-term business model, or does it threaten to replace it?

This shift reflects the massive financial stakes involved. At one point earlier this year, enterprise software companies collectively lost nearly $1 trillion in market capitalization within a single week, highlighting the volatility surrounding AI’s impact on the sector.

Which Software Companies Are Safer in the AI Era

Chen believes the answer largely depends on the type of software a company produces.

Some software systems perform highly deterministic functions where precision and reliability are critical. These include applications used for tasks such as payroll processing, accounting, financial reporting, billing, or compliance management.

In these areas, even small inaccuracies can cause serious problems. For example, an error rate of just 1% or 2% could create regulatory issues, accounting discrepancies, or legal liabilities.

Because of these strict requirements, Chen argues that companies operating in these segments still maintain strong competitive advantages and technological “moats.” Artificial intelligence may enhance their products but is unlikely to fully replace them.

However, companies whose software primarily aggregates public information and presents it through a user interface may face far greater disruption. AI models are increasingly capable of collecting, analyzing and presenting data directly, potentially bypassing traditional software layers.

For those firms, the competitive pressure could be severe.

Chen summarized the transformation succinctly: artificial intelligence is not eliminating software altogether, but it is fundamentally reshaping the hierarchy of winners and losers.

Leadership Is Also Changing Inside Tech Companies

The rapid shift toward AI-native technology stacks is also influencing how companies choose their leaders.

Chen noted that corporate boards are increasingly favoring executives with strong product and engineering backgrounds rather than those primarily focused on sales or marketing.

In previous decades, software companies could scale successfully with strong go-to-market strategies and large enterprise sales teams. But the AI era requires deep technical reinvention of products and platforms.

Companies attempting to rebuild their architecture around AI models, automation agents, and cloud-based data pipelines often need leaders who understand the underlying technology.

As a result, product-focused CEOs and technically experienced founders are becoming more attractive to investors and boards.

The change reflects a broader realization that artificial intelligence is not simply a feature that can be added to existing software. In many cases, it requires a complete redesign of how applications are built and delivered.

The Rise of “Software for AI Agents”

Another emerging trend discussed at the conference is the idea that the future customer for many software platforms may not be human at all.

The concept was described by CNBC producer Jasmine Wu as a shift from Software as a Service (SaaS) to what some industry leaders jokingly call “Software for Agents as a Service.”

The idea is that autonomous AI agents — rather than people — will increasingly interact with digital platforms.

For example, AI agents could automatically manage workflows, retrieve documents, schedule meetings, analyze contracts, or interact with enterprise systems on behalf of users.

Box CEO Aaron Levie has suggested that the market for software designed specifically for AI agents could eventually become ten times larger than the current market serving human users.

If that prediction proves correct, many existing enterprise software platforms will need to redesign their products to support AI-driven interactions rather than traditional user interfaces.

AI Infrastructure Spending May Be Near Its Peak

While software companies are racing to integrate AI, massive investment is still flowing into the infrastructure that powers these systems.

Major cloud providers and hyperscale technology companies have spent hundreds of billions of dollars building AI data centers filled with advanced processors and networking hardware.

Chen was asked whether infrastructure spending will continue accelerating through the end of the decade. His answer suggested that the industry may be approaching a plateau.

He expects spending levels around 2027 to remain roughly similar to current levels rather than expanding dramatically further.

If that outlook proves accurate, it could signal that the most aggressive phase of the AI capital expenditure cycle is nearing its peak, at least among the largest cloud providers.

However, new investment opportunities may emerge in companies developing solutions for key bottlenecks in the AI ecosystem.

New Opportunities Emerging Across the Tech Supply Chain

Despite the intense competition in enterprise software, Chen highlighted several areas that could see strong growth as artificial intelligence adoption expands.

One major beneficiary is cybersecurity. As AI systems become embedded in critical business operations, protecting data, infrastructure, and AI models themselves becomes increasingly important.

Cybersecurity companies already possess strong technological barriers to entry and may become even more essential as organizations deploy AI-powered systems across their operations.

Chen also pointed to emerging companies developing next-generation semiconductor technologies and advanced computing systems.

These firms are working to address key constraints in the AI ecosystem, including limited computing capacity, networking bandwidth limitations, and massive energy demands from data centers.

As artificial intelligence models grow larger and more complex, solving these infrastructure challenges could become a major industry opportunity.

AI Is No Longer Just a Future Vision

The broader message from the conference was clear: artificial intelligence is no longer a theoretical future opportunity.

For years, technology companies spoke about AI as a transformational idea that would eventually reshape industries. Today, investors and executives alike recognize that the transformation is already happening.

Companies are no longer rewarded simply for talking about artificial intelligence. Investors want concrete evidence that businesses are integrating AI deeply into their products, services, and long-term strategies.

Those that successfully adapt could lead the next generation of the software industry. Those that hesitate may find themselves overtaken in a rapidly changing technological landscape.