Synarchy Consulting’s Ramki Jayaraman on boards’ expectations as AI reshapes decision making
Jayaraman shares his perspective on how the consulting industry is evolving, where organisations are still struggling with AI and data readiness, and what leaders should focus on as they plan for 2026
03 February, 2026
TT
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As consulting adapts to a world shaped by AI, faster decision-making and rising expectations from boards, its role is changing. Clients are no longer looking for long reports, but for clear judgment and results they can act on. Ramki Jayaraman, managing partner at Synarchy Consulting, has spent the past few years working closely with leadership teams across the Middle East and Africa on strategy, operating models and data-led transformation.
Here, he shares his perspective on how the consulting industry is evolving, where organisations are still struggling with AI and data readiness, and what leaders should focus on as they plan for 2026.
What major trends marked the consulting industry across 2025, and which of those do you expect to accelerate or fade in 2026?
Across 2025, the most visible shift in consulting was the move from expert-only insight to insight at scale. Clients no longer expect consulting firms to be the sole source of analysis. Data, benchmarks, and even first-pass thinking are now widely accessible. What clients increasingly demand instead is evidence-led recommendations, faster synthesis, and greater precision in how insights are translated into decisions.
In parallel, GenAI has moved from experimentation to becoming a practical productivity layer. Leading firms are using it to accelerate research, structure problem statements, create first drafts of hypotheses, and stress-test scenarios. The firms pulling ahead are not those replacing judgment with automation, but those using AI to compress cycle times while strengthening quality control through governance, review discipline, and reusable knowledge assets.
In 2026, I expect three trends to accelerate meaningfully. First, AI-enabled delivery models will mature. We will see smaller, sharper teams delivering disproportionate impact, supported by reusable accelerators, agentic workflows, and domain-specific data products. Second, outcome-based engagements will expand. Clients are increasingly paying for measurable results, revenue uplift, cost-to-serve reduction, and cycle-time improvement, rather than the volume of slides produced. Third, industry-specialised transformation will continue to outpace generic strategy work, particularly in sectors such as government services, financial services, energy, logistics, and industrials.
What will fade is the traditional report-driven culture, where months are spent perfecting a document as the primary output. Boards and CEOs still value clarity and rigour, but they want decisions and execution momentum in weeks, not quarters. Consulting will remain anchored in structured problem-solving, but the unit of value is shifting decisively from the report to the result, with AI compressing the path from insight to implementation.
As AI, automation and data analytics become core to operations, what are the biggest capability or governance gaps you still see in regional organisations — and how should leaders close them?
The most common gaps I see in the region are not about ambition; they are about readiness and operating discipline. The first gap is data readiness. Many organisations still struggle with fragmented data ownership, inconsistent definitions, weak lineage, and limited interoperability across business units. There is a strong appetite for advanced analytics, but many enterprises are still operating on “spreadsheet truth” and duplicated systems.
The second gap is business-led AI. Too many initiatives are framed as technology experiments rather than business transformations. Without clear outcomes, accountable owners, and process redesign, these initiatives struggle to generate sustained value.
A third and very persistent gap is the “POC trap” — strong pilots that never scale. This typically happens because organisations have not designed an AI-ready product and operating model. Model monitoring, change management, process controls, cybersecurity, and long-term talent ownership are often afterthoughts rather than foundational elements.
Finally, governance is frequently miscalibrated. In some cases, it is too light, exposing organisations to risk. In others, it is so heavy that innovation stalls. What is needed is a pragmatic middle ground: clear policies, faster decision rights, and measurable performance guardrails.
Leaders can close these gaps with a structured approach. Start with a comprehensive AI diagnostic that spans business priorities, data maturity, target architecture, risk and compliance requirements, and organisational readiness. Translate this into a small number of outcome-defined use cases with named owners, ROI logic, and scale pathways. Build a fit-for-purpose governance model, covering model risk management, data stewardship, and ethical guidelines — and embed it into day-to-day operations rather than isolating it within a separate committee. Most importantly, invest in capability building: product owners, data engineers, process experts, and change leaders who can take AI from concept to enterprise value.
Middle East companies are prioritising operational resilience and scalability. What practical steps should boards and C-suite teams be taking now to make those priorities real, not just aspirational?
Operational resilience and scalability become real when leadership treats them as an operating system, not a slogan. Boards and C-suites should begin by clearly defining their non-negotiables, ervice continuity, regulatory compliance, cybersecurity posture, and cash-flow resilience under stress scenarios.
From there, the first practical step is to map critical value streams end-to-end, from procurement to delivery to after-sales, and identify single points of failure, manual bottlenecks, supplier concentration risks, and key-person dependencies. This exercise often reveals risks that dashboards alone do not surface.
Second, resilience requires decision-ready management information. Many organisations have dashboards, but very few have decision systems. Leaders should define a small set of operational KPIs that link directly to risk triggers and escalation playbooks, such as inventory coverage, supplier lead-time variance, plant uptime, order-cycle time, incident response metrics, and working-capital movement. This needs to be paired with a governance cadence that forces action: weekly operational reviews and quarterly scenario refreshes, rather than annual strategy off-sites.
Third, scalability depends on standardisation combined with modularity. Core processes should be standardised where control matters, finance, procurement, and data definitions, while modular components such as shared services, cloud platforms, reusable automation, and repeatable go-to-market motions enable scale across geographies or business lines.
In the GCC context, resilience also has a strong local dimension. As the region accelerates diversification beyond hydrocarbons, companies must strengthen local supply ecosystems, industrial partnerships, and capabilities that support “make in UAE” and “make in KSA” competitiveness. The organisations that succeed will be those that build durable operations today while positioning themselves for export-led growth tomorrow.
Which emerging technologies or strategic shifts should regional businesses prioritise to remain competitive and which are overhyped?
Regional businesses should prioritise technologies that move core business outcomes — revenue growth, customer experience, operating efficiency, and risk reduction. The highest-return opportunity right now lies in industry-specific AI use cases embedded directly into core operations.
For many organisations, the best starting point is revenue-focused AI: sales augmentation, pricing and promotion optimisation, customer segmentation, churn reduction, demand forecasting, and faster proposal or tender responses. Once value is proven, organisations can expand into efficiency-focused use cases across finance, procurement, HR, customer operations, and maintenance.
The second priority is cloud-native foundations, not as an IT upgrade, but as a business agility enabler. Cloud-native architectures, API-led integration, and modern data platforms make it feasible to scale analytics responsibly, reduce time-to-market, and support new digital products. Third, process automation with controls, including workflow, selective RPA, and AI-enabled decisioning, can unlock meaningful cycle-time reduction and compliance improvement when paired with process redesign and accountability.
What is overhyped is the belief that GenAI alone constitutes transformation. Many organisations are chasing generic copilots and chat interfaces without fixing data quality, workflow design, or adoption. The result is fragmented pilots and unclear ROI. Another overhyped pattern is technology-first roadmaps, where tools are deployed before outcomes, operating model changes, and governance are defined.
The organisations that win in 2026 will treat AI like a product portfolio: a small number of high-impact use cases, strong data and governance foundations, and an execution engine that takes initiatives beyond POC into scaled value. Anything that cannot explain its path to enterprise adoption should be treated with healthy scepticism.
How are regional economic policy changes, geopolitical tensions, and national diversification agendas in the UAE and Saudi Arabia reshaping advisory demand?
The UAE and Saudi diversification agendas are reshaping advisory demand in very concrete ways. They are accelerating investment cycles, raising the bar on competitiveness, and expanding the definition of transformation itself. Demand is shifting from pure efficiency programmes to strategic reinvention — including new growth platforms, industrial development, and capability building aligned with national priorities such as advanced manufacturing, logistics, digital government, and future-ready workforce strategies.
Geopolitical uncertainty and global supply-chain volatility are also sharpening the focus on resilience. Boards are increasingly seeking guidance on multi-sourcing strategies, localisation, critical-infrastructure readiness, cybersecurity, and regulatory compliance. Scenario-based planning that links macro signals to business decisions is becoming a core expectation rather than a specialist exercise.
Policy shifts are also accelerating the professionalisation of organisations. We see sustained demand for feasibility studies, business model design, and strategy-to-execution programmes, particularly where organisations are entering new sectors, building regional champions, or scaling cross-border. AI strategy and operating model design are also rising rapidly on board agendas, especially as regulators and stakeholders place greater emphasis on data governance, model risk, and responsible AI.
For advisory firms, the implication is clear: clients want partners who can integrate strategy, operating model, technology architecture, and governance into one cohesive transformation journey. In 2026 and beyond, demand will concentrate at the intersection of diversification, productivity, and digital capability — with faster delivery cycles and clearer accountability.
Family offices and Emirati families are playing a growing role in regional capital flows. How do their priorities differ from those of institutional investors, and how should advisers adapt?
Family offices and Emirati family investors bring a distinct lens to capital deployment. Financial returns matter, but so do legacy, continuity, reputation, and strategic relevance to the family’s broader business ecosystem. Compared to institutional investors, who operate under defined mandates, liquidity expectations, and structured risk frameworks, family offices often deploy patient capital.
Historically, many family investors have preferred asset-heavy and control-oriented investments such as real estate, industrial ventures, and joint ventures. What is changing is a more active engagement with growth-stage opportunities, including Series A and Series B investments, as families seek diversification and innovation adjacency to existing sectors.
Advisers need to adapt in three ways. First, focus on alignment and narrative. Family investors respond strongly to a clear story of strategic fit, risk containment, and long-term value creation. Second, strengthen governance and transparency. Investment theses must be backed by robust diligence, operating KPIs, and clear decision rights. Third, design structured deployment pathways, staged investments, milestone-linked funding, co-investment models, and partnership structures that respect family dynamics and confidentiality.
Ultimately, the most effective advisers in this segment combine strategic judgment with high-trust engagement. The best deal is not necessarily the one with the highest IRR, but the one that fits the family’s time horizon, values, and risk appetite while building sustainable capability.
How are investors, stakeholders and ecosystem partners reframing risk assessment today and what signals do they watch most closely?
Risk assessment in the region has become more dynamic and execution-focused. The question is no longer “Is this a good idea?” but “Can this organisation deliver, under real-world constraints, and how quickly will value materialise?”
The first signal investors examine is strategic alignment: whether the programme aligns with government agendas, regulatory direction, and sector tailwinds. In the Middle East, policy narratives significantly influence confidence and partnership momentum. The second signal is financial resilience: cash-flow durability, funding capacity, working-capital impact, and shock absorption under volatile conditions.
Execution readiness is the third major signal. Stakeholders look for credible sponsorship, clear decision rights, a capable PMO, and a proven ability to implement change. Fourth is technology and data feasibility: data foundations, cybersecurity integration, and scalable architecture. With AI, there is heightened scrutiny on governance — including model risk management and ethical considerations.
Finally, time-to-value has become critical. Programmes that deliver early, measurable wins without compromising control are perceived as lower risk. The strongest transformation proposals, therefore, combine ambition with sequencing: clear milestones, quantified benefits, risk controls, and transparent reporting that supports board-level decisions.
What differentiates Synarchy’s approach to digital and AI-enabled transformation in MEA?
Synarchy’s approach is grounded in a simple belief: AI transformation succeeds when it starts with business reality, not technology excitement. We begin with a robust AI readiness assessment covering business priorities, data maturity, technology landscape, governance requirements, and people readiness. In MEA, where regulatory expectations, legacy systems, and operating models vary widely, context matters deeply.
Our methodology spans four dimensions: business value, data and information architecture, technology ecosystem, and people and culture. From this, we design pragmatic roadmaps that balance near-term wins with long-term capability building. Importantly, we treat AI as an operating model shift, addressing decision rights, processes, controls, and adoption, not just models.
We are outcomes-oriented. We prioritise use cases tied to measurable value and design clear scale pathways beyond pilots. Our partnership model is long-term: advisory design, onboarding of AI solutions and governance, and implementation oversight to ensure adoption, performance monitoring, and value realisation. In short, we partner to deliver outcomes, not frameworks.
Can you share Synarchy’s near-term plans for expansion and capability buildout for 2026?
Our 2026 expansion is shaped by a consistent message from leadership teams: AI alone does not create advantage — organisations must be redesigned to move faster, decide better, and scale with confidence.
Geographically, we are expanding our presence in Abu Dhabi and progressing our Africa agenda, aligned with rising demand in government and key industries. Capability-wise, we are strengthening our offering in organisational and operating model design, helping clients clarify decision rights, streamline governance, redesign functions, and establish execution rhythms that match AI-compressed cycle times.
We are also deepening our full-stack AI advisory, but with sharper integration into the operating model change. This means linking AI initiatives directly to process redesign, talent deployment, and measurable performance outcomes. A third pillar of our buildout is long-term capability development — leadership upskilling, internal talent pipelines, and sustainable operating models.
Our focus is clear: combining strategy with execution, and AI transformation with organisational agility — so clients are not just transformed once, but are built to adapt continuously.
