Top 10 opportunities for technology companies in 2025

1. Deliver on the promise of AI

Transform potential into performance

The evolution of AI usage in businesses is reaching a tipping point. Experimentation with use cases and copilots has given way to expectations of returns on investments. As we enter 2025, the honeymoon period is over. Companies across industries are looking for tangible, positive returns from their AI spending.

The next step for tech companies is to prove the business value of AI by driving measurable return on investment (ROI) for customers. Tech companies should prioritize creating frameworks to measure the financial and operational impact of their AI solutions so customers can bridge the current gap between AI deployment and ROI realization. Those that succeed in demonstrating and delivering transparent, quantifiable value from their AI offerings will gain the trust of customers – and stand out in the competitive, AI-focused market of the future.

2. Drive growth and optimize customer experience through an agentic AI future

Harness next-generation, semi-autonomous AI “agents” to create new customer offerings.

Agentic AI represents a seismic shift for tech companies. Autonomous AI agents have the potential to execute complex tasks independently, revolutionizing how tech companies and their customers operate their businesses and make decisions. Unlike current forms of GenAI use cases, agentic AI doesn’t wait for prompts and instead presses forward with executing complex sequences of steps without human intervention, enabling the AI agent to complete tasks end-to-end. For example, agentic AI creates the potential to optimize customer service and marketing functions by analyzing vast amounts of data generated during customer interactions and then enabling personalized product and service offers. And when combined with additional data around market trends and competitor offerings, agentic AI can build the foundation for companies to adopt new dynamic pricing and outcome-based value models. The time is now for tech companies to seize the agentic AI opportunity and seize an early-mover advantage.

3. Adopt outcome-based pricing models to supplement subscription and consumption offerings

Get ahead of customer expectations with pricing that corresponds to customer value realization.

Source: Agentic AI: how SaaS companies can embrace the future (via ey.com US)

Over the years the tech industry has undergone a transition to as-a-service and consumption models. These models are currently under scrutiny from customers who increasingly expect demonstrable success from products purchased. This requires a mindset shift to selling success versus selling access or usage.

The next step in this pricing journey is value-based or outcome-based pricing, which is well aligned with the platform shift to agentic AI. However, this shift to outcome-based pricing raises several complex questions which require significant planning, data analysis, scenario planning and change management. This shift will also require significant levels of communication and engagement with stakeholders, even more so than when companies pivoted from selling perpetual licenses to charging on an as-a-service basis. During the as-a-service shift, many tech companies experienced challenges in communicating the rationale and value of that change to the markets and stakeholders, including internal sales teams whose incentive structures changed.

Based on this prior experience, it’s important that as tech companies plan their move to outcome-based pricing, they assess the product value delivered versus costs to acquire and deliver. It is equally important to explain the change in financial results, sales incentives and key metrics to influence and manage stakeholders’ expectations.

4. Demonstrate the power of an AI-first operating model

Rethink business models and processes to boost operational agility driven from AI.

Source: Six pillars of AI success for the C-suite (via ey.com US)

For several years much of the talk in the tech industry was about the competitive advantage born-digital companies enjoyed over legacy tech incumbents. Now the debate shifts to AI-born companies and their distinctive architecture and operating culture.

To compete with these AI start-ups, rather than bolting on AI to an existing operating model, tech companies should rethink and challenge all aspects of their operations. Here agentic AI can be an enabler of transformation by fostering cross-departmental collaboration as opposed to enhancing specific functions via individual GenAI use cases. For example, AI agents can build resiliency within supply chains by analyzing large supplier bases, identifying critical suppliers, creating simulation scenarios like natural disasters, supply shortages, or trade requirements and modeling contractual clauses and adjustments to ensure continuity and cost and tax optimization.

Benefits like these will increasingly span the enterprise, extending the capabilities of procurement managers, tax and legal professionals and finance professionals, among others, into better decision making to create new competitive advantages.

5. Unlock the value of data

Assess opportunities to modernize and consolidate legacy systems to better harness the power of enterprise data.

6. Empower your workforce of the future with innovative training

Boost productivity and evolve skill sets for the era of AI.

Source: Businesses can stop rising AI use from fueling anxiety (via ey.com US)

As tech companies progress toward building their AI-centered business future state, they can help drive growth by empowering their workforce with future-ready skills learned through targeted training programs. Embracing copilots and more advanced AI assistants can increase productivity while enhancing new ways of working at a more personalized level. By moving to more immersive training and learning environments like virtual and augmented reality, tech companies can better assess skill gaps, provide on-the-job support, identify unique talent across the globe, and ensure employee experiences are consistent, available on-demand, and fit-for-purpose.

As AI adoption continues, tech companies should expect more investor focus on cost efficiency metrics while employees demand a culture of continuous learning in and through the use of emerging technologies. Embedding GenAI as part of training culture will support both aims.

7. Embed tax and legal functions at the outset of AI transformations

Improve strategic decision making by addressing rapid changes in tax, trade and compliance requirements by addressing them up front – not as an afterthought – to optimize business models and supply chains.

Tech companies invest heavily to ensure acceptable certainty over their tax and legal responsibilities. But in today’s complex, shifting global tax and regulatory environment, this certainty is lacking – a situation exacerbated by the current geopolitical and trade implications of competing government agendas and policy initiatives around the world. An increasingly uncertain environment means treating tax or local regulatory issues as an afterthought – particularly when pursuing a transaction or making an AI-driven operating model shift – is an approach that’s now fraught with risk. Instead, tax and legal professionals should be viewed as strategic advisors to the C-Suite and embedded into the strategic evaluation process so decisions can be made confidently, at pace, and without creating unforeseen tax or legal liabilities.

The effects of tax and legal uncertainty are especially profound when it comes to managing today’s global supply chains. Tech companies need to re-examine their geographical dependencies and consider regional diversification to mitigate risks from geopolitical, regulatory and tax policy shifts. Additional trade restrictions will affect the entire value chain, making multi-sourced supply insufficient and requiring action to maintain or enhance resiliency. Steps like shifting production locations, stress-testing supply chains and securing strategic alliances may be needed to ensure stability and mitigate risk. And embedding AI into supply chain management can support all these strategies, while also improving operational agility and reducing costs. By embedding tax and legal functions at the outset of these strategic decisions, tech companies can help ensure compliance with regional regulations and tax policies.

8. Inject AI into cyber defenses

Tech companies that embed AI-driven security solutions will not only protect their assets but also position themselves in the market as leaders in trusted innovation.

Source: EY 2024 Global Cybersecurity Leadership Insights Study

A key aspect of the promise of AI is more effective and comprehensive cybersecurity through automating threat and vulnerability detection and response. Integrating AI-enabled security into products, services and operations from the outset not only enables companies to leverage high-quality security as a differentiator in the market, but also minimizes the related workload and impacts on the backend.

At the enterprise level, companies can benefit from implementing an integrated, proactive AI-driven cybersecurity strategy that features ongoing stress tests, learning and adaptation to stay ahead of the next threat or black swan event. Safeguarding sensitive information with advanced cybersecurity solutions is especially pivotal with autonomous systems, where ensuring data integrity is paramount.

However, the flipside of these AI advantages for tech companies’ cybersecurity defenses is that these same tools are available to their cyber adversaries. Bad actors can use AI to accelerate their ability to identify vulnerabilities that companies may have neglected and to penetrate their systems. This makes it all the more important to fight fire with fire, by using AI to proactively counter those threats and maximize incident response when breaches occur. Going forward, the quest for ever more effective ways to use AI in cybersecurity will remain a central focus for the industry – and a major opportunity for those that do this well.

9. Move beyond contingency funds to free up capital to invest in emerging technologies

Free up resources by divesting non-core businesses/products to invest in high growth opportunities and drive sustainable growth.

Significant investments in AI capabilities are contributing to higher valuations for tech companies, but they impose significant costs which put CapEx and Opex budgets under significant strain. Many tech companies initially used contingency and transformation budgets to fund early AI investments. Recently, many have resorted to holding operating budgets flat or making incremental cuts to fund ongoing AI investments. However, these short-fix approaches are no longer sufficient as AI becomes core to a tech company’s operations.

As we enter a period where market participants anticipate regulators to be more inclined to accept – or in some cases even encourage M&A — 2025 may be a moment for tech companies to free up capital for high-growth opportunities like AI through optimization of their portfolio via targeted strategic divestitures. In addition to raising capital, we find divestitures tend to create more focused, agile and streamlined operations which are better suited to sustainable AI investing. This strategy requires data-driven portfolio reassessments to identify underperforming assets and tech companies should ensure the alignment of any potential deals with their strategic goals, technological potential and market relevance.

10. Shape the agenda with incoming regulators

Actively engage with regulatory bodies to structure future frameworks and drive more consistency in regulatory outcomes.

Regulatory oversight and government engagement tended to historically focus on the largest tech companies, with smaller companies focused on compliance and less engagement. Recently governments worldwide have become more active and expansive in developing policies around several topics which impact tech companies such as AI, anti-trust, data privacy, cybersecurity, minimum tax rates and M&A. By collaborating with policymakers and proactively participating in international forums and global tax policy debates, tech companies of all sizes can help shape regulatory frameworks which foster innovation while still addressing societal concerns.

Advocacy for harmonized global standards, responsible AI guidelines and infrastructure investment incentives can also position tech companies as thought leaders and collaborators in public-private initiatives. This engagement can lead to more favorable regulatory environments and help build trust with stakeholders.