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Automation Anywhere appoints srikanth iyengar as head of EMEA growth to scale ai-powered enterprise automation across the region. Janvier Nshimyumuremyi June 16, 2026 Automation Anywhere EMEA growth: scale AI automation. Across Europe, the Middle East, and Africa, enterprises are under pressure to deliver faster service, tighter compliance, and measurable efficiency - without adding headcount. The strategic push for Automation Anywhere EMEA growth matters because it signals a more focused go-to-market approach for scaling intelligent automation where complexity is highest: regulated industries, multilingual operations, and distributed shared services. Business problem: fragmented operations limit scale. Many organizations in EMEA have modernized customer channels and core systems, yet day-to-day execution still depends on manual handoffs. Finance teams reconcile data across ERPs. Customer support rekeys information between CRM and ticketing. Risk and compliance groups chase audit trails across email threads and spreadsheets. These gaps create three persistent issues: slow cycle times, inconsistent outcomes, and limited visibility into process performance. Leaders trying to drive transformation often hit a predictable barrier: automation initiatives remain siloed. Without governance, reusable components, and business-aligned prioritization, workflow automation turns into a patchwork of scripts rather than a scalable operating model. AI solution: Automation Anywhere EMEA growth enables intelligent automation at scale. Automation Anywhere EMEA growth is closely tied to a broader shift in enterprise automation: moving from task bots to AI-powered automation that is designed, governed, and measured as a business capability. Instead of automating isolated steps, intelligent automation orchestrates end-to-end workflows, combines structured and unstructured data handling, and supports human-in-the-loop decisioning where needed. What "scale" should mean for automation leaders. Scaling is not simply deploying more bots. It is establishing repeatable delivery and measurable outcomes across regions, functions, and regulatory environments. * Standardization: reusable automation components and templates that reduce build time * Governance: role-based controls, auditability, and lifecycle management for risk-sensitive processes * Value engineering: prioritization based on AI-driven ROI, not stakeholder preference * Operational visibility: analytics to track throughput, exception rates, and savings realized Real-World application: high-value use cases for EMEA enterprises. For EMEA-based organizations, the best early wins typically sit where volume is high and variability is manageable. Intelligent automation can be applied to streamline cross-system work, reduce errors, and improve response time while maintaining compliance. Practical automation candidates. * Order-to-cash: automate invoice creation, dispute triage, and remittance matching to improve cash flow * Know-your-customer and onboarding: extract required fields, validate documents, and route exceptions for review * IT service operations: accelerate password resets, access provisioning, and incident enrichment for faster resolution * Procure-to-pay: automate PO matching, vendor master updates, and approvals to reduce leakage In each case, the goal is process optimization that improves speed and consistency while creating a clean audit trail - particularly important in financial services, healthcare, telecom, and public sector environments. Business impact: from cost reduction to competitive resilience. When executed as a scaled program, automation improves operational efficiency in ways that leaders can quantify: reduced rework, fewer compliance exceptions, faster turnaround times, and better employee utilization. Done well, it also increases resilience - teams can absorb demand spikes without compromising customer experience. To maximize results, treat automation as a portfolio. Establish baseline metrics (cycle time, error rate, cost per transaction), then track gains post-deployment. This approach makes benefits defensible to CFOs and audit committees, while enabling continuous improvement. Actionable decision insight: what to do next. If you're building an automation roadmap, use this decision filter: prioritize processes with clear volume, stable rules, and measurable outcomes; then expand into more judgment-heavy workflows as governance matures. Align stakeholders on an operating model early - CoE structure, intake, standards, and value tracking - so automation becomes a scalable capability, not a series of pilots. To learn more about the strategic direction behind Automation Anywhere EMEA growth, read the announcement here. Ultimately, Automation Anywhere EMEA growth is a signal that enterprise automation in the region is moving into a more outcome-driven phase - where intelligent automation, governance, and measurable ROI determine who scales successfully and who stalls at experimentation. Survey: Nearly All European Organisations...

Former Automation Anywhere executive joins Tecnoprism to scale ai-driven enterprise automation. Jun 08,2026 By Priyanka Shinde Daljeet Singh, former Sales Director at Automation Anywhere, has joined Tecnoprism as Co-Founder, bringing with him rare, first-hand experience of building and scaling enterprise automation across Fortune 100 organizations - from the industry's pre-RPA origins to its current shift toward AI-led operations. His move signals a critical shift for enterprises already invested in automation: the focus is rapidly moving from deploying bots to building intelligent, integrated systems that can operate at scale in increasingly complex environments. Singh was part of Automation Anywhere during its formative years, well before enterprise automation became mainstream, and has since contributed to scaling automation adoption across global organizations into enterprise-grade programs. Enterprises are now confronting the limits of automation built in isolation, where increasing bot deployments alone no longer deliver proportional business value. The shift underway is toward operating models that combine execution with intelligence, enabling systems to make decisions and adapt across functions. Recent Forrester research reflects this transition, noting that while AI adoption is accelerating across enterprises, fragmented systems and a lack of orchestration continue to limit its full impact, pushing organizations toward more integrated automation strategies. "What we are seeing now is not an extension of automation; it's a transition," said Daljeet Singh, Co-Founder, Tecnoprism. "Enterprises have already automated processes at scale, but the next challenge is fundamentally different. Gartner highlights that organizations are increasingly relying on AI-driven automation to improve resilience and handle rising operational complexity. The real shift is no longer execution; it's how systems think, adapt, and operate cohesively across functions," Singh added. At Tecnoprism, Singh is focused on building a unified approach that combines automation, artificial intelligence, and orchestration, enabling enterprises to move beyond fragmented deployments toward intelligent, scalable, and outcome-driven operations. Tecnoprism has already delivered programs at scale across enterprise environments, with over 6.9 million hours saved, 720+ use cases automated, 1200+ active bots in BFSI, and 350+ AI agents deployed, reflecting deep experience in managing large and complex automation ecosystems. This direction was further reinforced with Singh's introduction of the "CFO Handbook" at CFO Confex & Awards 2026, which framed AI and automation as strategic levers for financial and operational transformation. The discussions highlighted a growing shift among enterprise leadership, from efficiency-led initiatives to intelligence-led operating models. He joins Tapan Patel, co-founder of Tecnoprism, who has been instrumental in shaping the company's foundation, building its enterprise-scale delivery capabilities, and driving its evolution into a next-generation AI and automation firm. Together, the founding team represents a convergence of industry-building experience and execution depth, positioning Tecnoprism to address the next phase of enterprise transformation. "Enterprises are no longer asking how to automate more; they are asking how to operate smarter," Singh added. "The future lies in systems that can combine automation and intelligence seamlessly. That is what we are building at Tecnoprism." Tecnoprism is expected to introduce additional capabilities in the coming months as it expands its AI and automation roadmap. About Tecnoprism. Tecnoprism is a pure-play AI and automation company focused on helping enterprises build intelligent, scalable operations. Founded by industry pioneers with more than three decades of combined automation experience, Tecnoprism brings deep intelligence, extensive experience, and enterprise-scale execution to global business operations. Backed by a team of 250+ AI and automation engineers and a global presence across North America, MENA, Southeast Asia, and APAC, Tecnoprism partners with enterprises and Fortune 500 companies, enabling them to move beyond isolated automation toward adaptive, outcome-driven systems.

Automation Anywhere reported that 61% of its fourth-quarter software bookings came from AI-powered offerings, as enterprises shift from experimentation to deploying AI solutions for core business functions. The company's agentic customer base more than doubled, driven by engineers converting AI pilots into scaled deployments. The AI automation provider saw double-digit year-over-year growth in both Annual Recurring Revenue and Remaining Performance Operations. Enterprise customers with over $1 million in ARR grew 23%, whilst the company achieved its 10th consecutive quarter of non-GAAP profitability and free cash flow. Automation Anywhere announced a strategic collaboration with OpenAI during the quarter and recently acquired Aisera to expand AI-driven solutions across IT service management, finance, customer service and HR functions.