The Middle East is entering a decisive period for business strategy. Capital is flowing into digital infrastructure, AI has become central to national agendas, and expectations for growth remain high. At the same time, scrutiny around returns, resilience, and sustainability is intensifying. Upgrading technology alone is no longer enough. Companies are being judged on their ability to translate innovation into sustained performance, manage rising energy demands, and develop talent that can work alongside intelligent systems. 

The question facing executives is not whether to invest, but how to structure organizations that can repeatedly adapt as technologies, markets, and regulations evolve. Long-term advantage will favor those who treat change as a core capability rather than a periodic initiative.

Andrew Smart, Senior Managing Director at Accenture Middle East, sees this divide as a question of scope and ambition. In his view, many organizations remain focused on improving existing systems rather than rethinking how the business operates end to end. Reinvention, as Accenture defines it, is a continuous capability that aligns strategy, technology, talent, and culture to deliver sustained performance. It is this shift, from isolated upgrades to a reimagined operating model, that determines whether digital investment becomes a growth driver or remains incremental.

AI ADOPTION AND READINESS

The Middle East is at a critical turning point for AI adoption, Smart says, driven by national strategies in markets such as the UAE and Saudi Arabia, where AI is positioned as a central pillar of economic diversification. Accenture’s research indicates the region is moving quickly, with “over 85 percent of Middle East businesses” reporting a reinvention strategy and most accelerating those efforts over the past year. Despite this progress, true AI maturity remains uneven.

While “C-suite interest and intent are high,” Smart notes that the number of “AI achievers” is still relatively small compared with global leaders. Many organizations remain focused on “pilots and experimentation rather than enterprise-wide scaling,” which limits the potential impact of their investments.

One capability that continues to be underestimated is sovereign AI. Smart explains that in a region aiming to build “culturally and linguistically attuned AI models while safeguarding national data,” sovereignty “goes beyond compliance” and can act as “a competitive accelerator.” Treated as a strategic asset, sovereign AI can help unlock trust, fuel local innovation, and accelerate growth, particularly when responsible AI practices, ongoing risk assessments, and systemic testing are embedded from the outset.

AI also has significant implications for energy systems. Smart says it offers “a generational leap forward in the productivity and efficiency of the world’s energy systems,” while simultaneously driving a surge in demand, mainly from new data centers. Organizations involved in energy provision are acutely aware of this dual opportunity and challenge, given the region’s net-zero commitments and diversification goals. Awareness, however, has not yet been fully translated into operational readiness.

Preparedness for the rapid increase in computational capacity, particularly from generative AI, “is still nascent,” Smart notes. Accenture’s Powered for Change research emphasizes the need for a “systemic, multigenerational approach,” moving companies away from bespoke, one-off infrastructure projects and toward repeatable, standardized systems designed for continuous learning and upgrading. For the Middle East, this approach means incorporating low-carbon energy sources, sustainable water use, and grid resilience into planning from the outset.

The scale of investment involved raises a key question: “What are we getting from the resources we’re investing in AI?” To address this, Accenture introduced the Sustainable AI Quotient, a metric that tracks how effectively AI converts money, energy, and emissions into performance. 

Smart highlights the need for “smarter, more energy-efficient silicon,” decarbonized data centers, thoughtful use of models to reduce waste, and embedding sustainability directly into AI governance. In the energy sector, the most significant gap remains the application of locally governed, real-time AI to the grid, a step Smart sees as crucial for improving resilience and lowering the cost of powering the region’s digital future.

BUILDING AN INTELLIGENT ENERGY SYSTEM

Meaningful integration between legacy energy systems and emerging low-carbon technologies relies on what Smart describes as “an intelligent energy system,” a unified, digitalized, and optimized ecosystem capable of seamlessly managing both traditional and renewable sources. The foundation of this system is a strengthened digital backbone. Legacy infrastructure, from wells and pipelines to refineries and distribution networks, must be equipped with “advanced sensors, IoT, and 5G connectivity” to create a continuous stream of real-time operational data.

That data then enables what Smart calls “carbon intelligence.” He explains, “Companies must treat carbon, energy, and emissions data with the same rigorous importance as financial and operational information.” By feeding operational data into AI and digital twin capabilities, organizations can optimize existing assets, dramatically reduce Scope 1 and 2 emissions, and determine where infrastructure should be retired or repurposed.

Decentralization is the final piece of the puzzle. Digital twins and advanced analytics enable companies to model and integrate decentralized energy resources, such as solar, wind, and battery storage, into the existing grid. Smart notes that this enables “real-time coordination, dynamic load balancing and predictive maintenance across the entire value chain,” ensuring that legacy systems support a transition to a resilient, efficient, and low-carbon energy future.

Despite rising investment in green energy, Smart identifies a frequently overlooked barrier: “not capital, ambition, or technology readiness; it is the lack of organizational delivery capacity and carbon intelligence required to connect energy diversification investments to tangible business value.” While many businesses have set ambitious targets, few have developed the internal data capabilities and operating models necessary to execute them at scale.

Companies often struggle to integrate emissions and energy consumption data into core business decisions, making it “impossible to prioritize, execute and scale decarbonization effectively.” Without real-time measurement of product-level carbon footprints, enterprises cannot make optimal choices regarding supply chain diversification or renewable energy sourcing.

Smart emphasizes that diversification is too often treated as “a cost center or a compliance exercise.” The organizations that succeed are those that use green energy to generate new business value. This can include cost savings from increased efficiency, the creation of low-carbon product lines, or enhanced investor confidence. Leadership, he argues, must view energy diversification as “a reinvention opportunity that drives growth, not just an obligation to fulfill.”

EMBEDDING INNOVATION INTO STRATEGY

Smart identifies the cultural shift defining the next era of innovation in the Middle East as “the move from episodic transformation to a continuous culture of reinvention.” The region has historically excelled at large, top-down, project-based initiatives. However, the future requires blending this approach with “bottom-up and permanent agility,” which enables organizations to continually reinvent themselves as markets and technologies evolve.

Innovation must extend beyond an “innovation lab” or a single department to become an institutionalized practice. Smart emphasizes that this entails integrating an innovation framework into corporate strategy, maintaining rigorous governance, and building internal ecosystems that foster collaboration between employees, partners, and customers.

Talent and skills are central to this transformation. “Technological transformation is only as effective as the workforce that wields it,” he says, highlighting the importance of cultivating a culture of continuous co-learning and upskilling. Employees must be equipped with future-ready skills to collaborate effectively with AI.

Smart adds that, given the young, digitally savvy population and the rapid pace of change highlighted by Accenture’s Pulse of Change Index, the organizations most likely to succeed will be those that not only accept change but actively seek it, embedding a continuous reinvention mindset into daily operations.

REINVENTION AS STRATEGIC IMPERATIVE

Leaders are being asked to rethink automation not simply as a means to reduce roles but as a tool to transform processes and business outcomes. Smart says this requires redesigning organizations to support new technologies while fostering continuous improvement, ultimately creating “entirely new, more valuable work models.”

Redefining roles is a critical starting point. “Instead of focusing on job titles, leaders must focus on tasks and capabilities,” he explains. AI may eliminate repetitive work, but it simultaneously opens opportunities in high-value areas such as prompt engineering, AI governance, creative synthesis, and complex problem-solving. Roles are shifting from execution to judgment, oversight, and value creation.

Unlocking potential also depends on the integration of a holistic operating model. True transformation arises from “an operating model that holistically integrates technology, talent, and processes,” where automation simplifies structures, reduces bureaucracy, and frees human capital for strategic work.

Talent development remains central. Smart notes that “leaders must invest heavily in personalized, scalable learning and upskilling programs” such as Accenture’s LearnVantage. This goes beyond technical skills to include human capabilities such as creativity, emotional intelligence, and critical thinking, which generative AI cannot replicate.

The future of work requires agility and fluidity, combining human and machine capabilities. According to Smart, it will be “a fluid, human-machine collaboration where talent is dynamically deployed based on strategic priorities and AI agents are seamlessly integrated into teams,” enabling employees to unlock greater potential and pursue more meaningful work.

Looking at the broader horizon, Smart identifies the defining theme for the next decade of business strategy in the Middle East as “Reinvention.” He says, “The scale of national diversification visions such as Saudi Arabia’s Vision 2030 are examples of reinvention. Businesses must mirror this national ambition by reinventing their own purpose, operations, and models.” Advanced AI, he adds, acts as “the most powerful catalyst we have seen in decades,” demanding a complete overhaul of the digital core, operating models, and talent strategies to capture new value.

Reinvention, Smart emphasizes, “captures the essence of the challenge faced by Middle Eastern companies not just to modernize or transform once, but to embed a continuous capability for change to stay ahead of the relentless pace of disruption and build resilience for long-term, profitable growth.” He views it as the strategic pathway linking government ambition, technological advancement, and the delivery of productivity, growth, and value across the region.