AI's 2026 Reality Check: New Report Reveals Industry Pressures

MONTREAL, QC – March 23, 2026 – As businesses chart their course for 2026, the era of experimental AI is officially over. A new industry report from digital transformation consultancy Alithya reveals that the focus has decisively shifted from hype to execution, with financial services, manufacturing, and healthcare leaders prioritizing measurable returns, robust data infrastructure, and pragmatic AI adoption to navigate a landscape of intense financial and operational pressure.

The latest edition of Alithya's sector-specific research program paints a picture of industries at a crossroads. While the promise of artificial intelligence remains a central pillar of long-term strategy, executives are now demanding tangible value. The findings underscore a critical pivot: success is no longer defined by launching AI pilots but by building resilient, data-driven organizations capable of translating technology investment into concrete business outcomes.

The AI Readiness Imperative: Beyond the Hype

The central theme emerging from the research is a widespread move toward pragmatism. The "honeymoon phase" for AI, where innovation was pursued for its own sake, has given way to a period of scrutiny where Chief Financial Officers are demanding clear return on investment. This sentiment aligns with broader market analysis suggesting that companies expect to see productivity gains, cost savings, or revenue growth from AI projects within a tight 6-to-12-month window.

This shift places immense pressure on organizations to ensure their foundational systems are prepared. According to Alithya's President and Chief Executive Officer, Paul Raymond, this is the most critical factor for success. "Technology, especially AI, is now at the center of every long‑term strategy," Raymond stated in the announcement. "But leaders are clear: AI only delivers value when built on strong data foundations."

This statement highlights a growing digital divide. The companies poised to lead in 2026 are those that have already invested heavily in modernizing their data architecture, ensuring data quality, and establishing clear governance. For others, the urgent task of "getting data AI-ready" has become the primary bottleneck, preventing them from scaling generative AI and other advanced technologies. The report suggests that investment in data and AI infrastructure is now the top priority for a majority of business leaders, reflecting a market-wide recognition that algorithms are only as good as the data they are fed.

Tailored Transformation: A Sector-Specific AI Roadmap

While the need for a strong data foundation is universal, Alithya's research demonstrates that AI strategy and adoption drivers diverge significantly across industries. A one-size-fits-all approach is proving ineffective, as each sector grapples with its own unique set of pressures and priorities.

In financial services, the primary challenge is managing immense enterprise complexity. Respondents in this sector are turning to a combination of cloud platforms, automation, and emerging agentic AI to streamline operations and enhance decision-making. Agentic AI, which can act as a proactive collaborator in business workflows, is gaining traction. However, the report also notes significant hurdles slowing the deployment of generative AI, likely stemming from stringent security requirements, regulatory uncertainty, and concerns over data privacy in a highly sensitive environment.

For the manufacturing sector, the focus is squarely on productivity, workforce modernization, and supply chain resiliency. Leaders are evaluating their AI readiness and building automation roadmaps to compete in a volatile global market. The adoption of technologies like Microsoft Copilot and predictive analytics is accelerating as manufacturers seek to enhance operational efficiency and mitigate disruptions. This push is a direct response to recent global events that have exposed vulnerabilities in traditional supply chains, making AI-supported decision-making a cornerstone of future competitiveness.

Meanwhile, the healthcare industry is contending with what the report calls "ongoing financial strain" and "persistent labor cost challenges." The pressures are felt by both payers and providers, but their investment priorities differ accordingly. Payers are emphasizing data modernization and advanced analytics to better manage risk and costs. Providers, on the other hand, cite an urgent need for systems that reduce the crushing administrative burden on clinicians. Technologies that can automate clinical documentation, streamline scheduling, and optimize workflows are seen as critical tools for achieving sustainable care delivery and combating workforce burnout.

Building the Foundation: From Strategy to Execution

The insights from the report effectively serve as a blueprint for the modern enterprise, outlining the capabilities required to compete. They also illuminate the market positioning of firms like Alithya, which are moving to fill the role of strategic advisor, helping organizations bridge the gap between their current state and their AI-powered future.

With deep expertise in platforms from major partners like Microsoft and Oracle, implementation specialists are crucial in building the technological backbone that the report identifies as essential. For instance, Alithya's recent recognition as a member of the Microsoft AI Business Solutions Inner Circle underscores the importance of partner ecosystems in deploying sophisticated tools like Dynamics 365 and Power Platform, which are often the engines of AI-driven transformation.

Success in this environment requires more than just technical proficiency. As demonstrated by recent large-scale Oracle Cloud and Microsoft D365 go-lives for clients in healthcare and manufacturing, the ability to manage complex implementations within specific industry contexts is paramount. The research confirms that organizations are seeking partners who not only understand the technology but can translate it into the measurable business outcomes—a sentiment that is increasingly separating successful consultancies from the rest of the pack in a crowded market.

The Road Ahead: Navigating Complexity and Governance

As organizations accelerate their AI adoption, they are also entering a new phase of complexity that extends beyond technology and into the realms of ethics, governance, and regulation. The path forward involves not only deploying AI systems but also ensuring they are explainable, trustworthy, and free from bias, particularly in high-stakes industries like healthcare and finance.

The findings released by Alithya provide a vital, data-driven snapshot of the priorities shaping enterprise strategy. They confirm that while the potential of AI is undisputed, its practical application is a challenging journey that demands careful planning, strategic investment, and a relentless focus on foundational strength. For businesses looking toward 2026, the message is clear: the race will be won not by the earliest adopters of AI, but by the most prepared.