Growth strategy under pressure: Can AI unlock what’s next?

AI has the potential to make companies more nimble and more sophisticated in how they serve customers, and to help them tap into new sources for growth. The issue is, most companies are focused on deploying AI as a tool for productivity and don’t yet trust it for growth initiatives. Overcoming this trust barrier may separate the leaders and laggards over the next several years.

Corporate growth leaders see this potential — and they are eager to figure out AI for growth. In fact, 78% of survey respondents said they believe that the rise of AI will ultimately accelerate their growth rate. While many see the rise of AI creating new market entrants (41%) or threats to existing revenue streams that could be supplanted by AI (34%), a far greater share of executives are optimistic about potential improvements in the way that they sell or serve customers (63%) or the development of new growth markets (57%).

The challenge is one of understanding, trust and readiness. Only 49% strongly agree that their organizations know how best to leverage data and AI to enable growth. Many are still unsure whether the technology itself is ready for the high-stakes commercial decisions that underlie growth strategy. Only about a third say that their organization would trust AI inputs to support decision-making in areas like optimizing pricing, new product or service development and assessing M&A targets.

The issue of readiness is not just about the evolution of the technology but barriers that companies allowed to develop within their own organizations. We gave executives a long list of obstacles to growth, including ever-present issues of stakeholder alignment and change management. But when ranking which of these issues were the greatest barrier to growth in today’s environment, the two they ranked highest are factors that speak directly to a company’s ability to make the most of AI: hurdles in their own risk and compliance, and challenges with their legacy technology infrastructure (including data).

Indeed, the lack of trust that corporate growth leaders express around using AI for growth decisions makes sense if their risk posture is slowing their ability to adopt and build on the latest frontier models, or if the data needed as context for the AI models is siloed across the organization. The survey respondents’ hesitation reflects the feedback we have heard on AI deployment: A far greater share of companies reported using AI for improving efficiency or productivity (63%) than for staying ahead of competitors (14%), reaching new customers (8%) or diversifying revenue streams (7%).

These findings reinforce a theme that is coming up increasingly in client conversations. The traditional tools of growth strategy — market analytics, where to play, how to win, customer insights — are today broadly embedded across corporate America. Companies are not leading on growth simply because they had an insight or idea their competitors lacked. Especially as we point toward an era of AI for growth, executives will only differentiate performance if they can align all elements of the organization (e.g., front and back office, risk and technology) to drive an AI-first growth agenda with speed.

The good news is that many of these barriers are also in the company’s control, including: finding or training the right talent; identifying and adding the technology in a targeted, efficient way; bringing together data on one platform; and establishing strong risk and compliance protocols. Getting these elements in order quickly is essential for scaling AI as a growth enabler.

For example, a $10 billion industrial products company had accumulated significant legacy debt with 19 separate enterprise resource planning (ERP) instances due to an aggressive inorganic growth strategy resulting in no visibility into customer, channel, or product profitability and declining growth. EY teams helped the company design, build and operate an AI-ready enterprise data platform in nine months to eliminate data silos, provide real-time visibility to the business on decision intelligence, and more importantly accelerate their AI strategy to build a trusted AI-first growth platform to create a competitive advantage.

The survey data reinforces much of the public narrative around AI: Most companies are largely focused on the potential for AI to drive productivity, efficiency and cost savings. Yet the data also shows the optimism of using AI for growth and that some leading-edge companies are beginning to explore these use cases. What are the opportunities that are being explored on that leading edge?

EY-Parthenon teams are working with clients on the frontier of leveraging AI for growth. Although the topic is nascent, several key themes are emerging.

1. Harnessing AI to mine a company’s intellectual property and patent data to help drive growth

Companies can then find new uses or products that can be developed and markets that can be addressed. For example, a large industrial products manufacturer recently engaged us to use our proprietary Intellectual Property Value Creation (IPVC) approach to analyze thousands of its patents and identify interesting new applications for those patents across their core business and in adjacent and disruptive markets.

2. Driving greater value from core systems

Most companies have already made significant investments in tools that have improved efficiency and control, but they have not materially changed their growth trajectories. Today’s enterprise is optimized around system-driven, function-by-function workflows. Pricing enforces rules rather than optimizing enterprise value, and sales is optimized to service demand, not expand it. The result is that transactions are executed efficiently, but systems lack the ability to reason across the trade-offs that drive profitable growth, e.g., margin vs. win-rate and growth vs. capacity. Recent advances in AI-based reasoning allow companies to separate decision intelligence from transactional systems, orchestrating actions across functions without replacing core systems and continuously learning from outcomes rather than relying on static rules.

Especially in the industrials sector, EY-Parthenon teams are working with clients to apply this shift across a range of growth-related functions. These include:

3. Tapping into the promise of neurosymbolic AI (NSAI)

As the survey demonstrates, the deployment of AI to drive growth decision-making is closely linked to executives’ comfort in trusting the output. For regulated industries, this imperative becomes even more acute; the trust of the C-suite alone is not sufficient if the company cannot demonstrate that AI-enabled decisions are consistent and compliant with regulatory standards.

This is why our work on NSAI has resonated so strongly with executives as an approach that could give them the confidence they need to deploy AI for growth. NSAI combines the same ability of neural networks to learn from structured and unstructured data with a symbolic layer of rules and parameters that create consistent, auditable and transparent results for decision-making. While executives fear hallucinations from standard large language models, NSAI not only creates auditable results but allows leaders to directly set the rules that will govern the model.

The potential applications for NSAI are vast, but EY-Parthenon teams have seen some of the most immediate interest in regulated sectors like insurance and banking. Some leadership teams in insurance are looking to use NSAI, for example, to dramatically expand their ability to assess large volumes of submissions, provide front-line underwriters with far better analytics focused on the most promising leads, and ultimately drive more profitable growth. Similarly, banking clients are seeking NSAI to power large-scale decisions related to consumer credit — where the market is looking for greater personalization — while banks must balance that against the multifaceted guardrails of risk appetite, portfolio limits and regulatory thresholds.

AI: the piece that completes the growth strategy mosaic

Growth strategy these days is much more fluid than it has been in the past, making long-term planning more difficult. Growth leaders know they need to take steps to adapt to the current environment.

It’s clear that executives can see the value of AI as a growth enabler but they are still unsure of how to deploy it. With today’s challenges to growth, the time for hesitation is over. Companies that move quickly to use AI to discover and support untapped growth opportunities can develop a competitive advantage over their less forward-thinking competition.