Newgen Software’s recent inclusion among the ‘Notable Vendors’ in Forrester’s Digital Process Automation Software Landscape for Q3 2026 marks a significant milestone for the company and signals broader shifts in the enterprise automation arena. The recognition comes at a time when organizations worldwide are under mounting pressure to deliver faster, more intelligent services while keeping costs in check and maintaining regulatory compliance. Forrester’s evaluation, which examined 39 vendors across the DPA spectrum, highlights the growing importance of platforms that do more than merely route tasks—they must embed advanced modeling, dynamic case management, and AI‑driven support into the very fabric of business operations. Newgen’s presence in this list underscores its ability to meet these heightened expectations, particularly in sectors where process complexity and regulatory oversight are historically high. Analysts note that the award reflects not just technological prowess but also a strategic vision that aligns with the emerging imperative to orchestrate intelligence across the enterprise rather than merely automating isolated tasks. For decision‑makers scanning the market, this recognition serves as a data‑point that Newgen’s platform is being viewed through the same rigorous lens used to assess the overall direction of the DPA space, offering a credible reference point when weighing investment options.
The Forrester report opens with a stark observation: enterprises are confronting an ‘automation imperative’ that is being powered by a wave of AI‑based optimism across industries. This optimism is not merely hype; it is rooted in tangible outcomes where machine learning models, natural language processors, and generative AI have begun to demonstrate measurable improvements in speed, accuracy, and customer satisfaction. Yet, the same data reveal a critical nuance—54 % of automation decision‑makers now say their organizations must shift focus from piecemeal workflow and task automation toward comprehensive, end‑to‑end process automation. This shift reflects a growing realization that isolated automation efforts, while useful for quick wins, often create silos that hinder scalability and obscure opportunities for deeper operational transformation. Decision‑makers are increasingly asking how to connect disparate bots, RPA scripts, and legacy systems into a cohesive intelligence layer that can adapt to changing business conditions. The report suggests that vendors capable of delivering a unified orchestration environment—where process, content, communication, and AI coexist—will be better positioned to meet this demand. For organizations evaluating their automation roadmaps, the implication is clear: investing in platforms that support end‑to‑end visibility and control is no longer optional but a strategic necessity to sustain competitive advantage.
At the heart of Forrester’s analysis lies the concept of agentic execution, a paradigm where AI agents dynamically construct work patterns based on real‑time context and evolving conditions, thereby augmenting traditional, fixed workflows. Unlike static process models that require manual re‑engineering whenever a rule changes, agentic agents observe data streams, infer intent, and autonomously adjust the sequence of activities to achieve desired outcomes. This capability enables enterprises to respond swiftly to exceptions, regulatory updates, or shifting customer expectations without invoking lengthy change‑control cycles. Forrester identifies agentic execution as the market’s main trend because it promises to bridge the gap between deterministic automation and the fluid, decision‑rich environments that modern businesses inhabit. The technology leverages reinforcement learning, contextual awareness, and goal‑oriented planning to create self‑optimizing processes that learn from experience. For vendors, the challenge lies in exposing these agents through transparent governance mechanisms so that business leaders retain oversight while benefitting from increased agility. For buyers, understanding how a platform implements agentic capabilities—its underlying AI models, explainability features, and integration points—is essential to assessing whether it can truly move beyond static workflows toward a living, adaptive operational fabric.
While the potential of AI‑embedded automation is exciting, Forrester also flags a primary challenge that many enterprises encounter when attempting to scale pilot projects into production‑grade solutions: the emergence of multisystem integration gaps, human‑interaction breakdowns, and regulatory compliance hurdles. In pilot phases, automation often runs within a sandboxed environment where data sources are limited, user interactions are simulated, and compliance checks are simplified. Moving to production introduces a complex web of legacy ERP systems, CRM platforms, document repositories, and external APIs that must communicate reliably and securely. Integration gaps appear when data formats differ, authentication mechanisms clash, or latency introduces bottlenecks that erode the promised efficiency gains. Simultaneously, human‑interaction breakdowns occur when automated steps fail to handoff gracefully to knowledge workers, leading to confusion, manual rework, or erosion of trust in the system. Finally, regulatory compliance becomes a moving target as industries such as finance, healthcare, and government impose stringent audit trails, data residency rules, and consent management requirements. Vendors that can provide built‑in connectors, robust error‑handling frameworks, and configurable compliance modules are better equipped to help customers navigate these obstacles. For organizations, the takeaway is to prioritize platforms that offer proven integration libraries, clear governance controls, and a track record of successful production deployments in highly regulated settings.
Forrester’s Landscape data situates Newgen with a geographic footprint that spans North America, EMEA, and APAC, reflecting a truly global go‑to‑market strategy that enables the company to serve multinational enterprises with consistent product versions and localized support. This breadth is especially valuable for organizations that operate across multiple jurisdictions and need a vendor capable of understanding regional nuances in data protection laws, industry‑specific regulations, and cultural business practices. In terms of industry focus, the report highlights Newgen’s concentration on financial services and insurance, government and public sector, and healthcare—three verticals where regulatory scrutiny is typically at its most intense and where long‑running case management processes are the norm. These sectors often involve lengthy approval cycles, extensive documentation requirements, and high stakes for data accuracy, making them ideal proving grounds for a platform that promises to unify content, process, and communications under a single intelligent orchestration layer. Newgen’s deep domain expertise in these areas translates into pre‑built accelerators, regulatory templates, and industry‑specific AI models that reduce implementation time and risk. For prospects evaluating vendors, aligning a provider’s industry focus with their own sector can be a decisive factor in achieving faster time‑to‑value and ensuring that the solution remains compliant as regulations evolve.
Another noteworthy aspect of Newgen’s profile in the Forrester Landscape is its ability to offer all three primary deployment models tracked in the report: hosted/private SaaS, multitenant SaaS, and on‑premises installations. This flexibility is not merely a technical footnote; it represents a strategic advantage for enterprises operating in regulated industries where data sovereignty, latency concerns, or existing infrastructure investments may dictate a particular deployment choice. Hosted/private SaaS offers a dedicated environment that can satisfy strict data‑isolation requirements while still delivering the operational benefits of a cloud‑based model. Multitenant SaaS provides rapid scalability and lower total cost of ownership for organizations comfortable with shared‑resource architectures. Meanwhile, on‑premises deployments remain essential for government agencies, financial institutions, and healthcare providers that must keep sensitive data within their own firewalls due to legal mandates or internal policies. By supporting all three models, Newgen enables customers to start with a deployment approach that matches their current constraints and later shift models as their needs evolve—without being forced into a costly re‑architecture or vendor lock‑in scenario. For decision‑makers, this adaptability reduces the risk associated with long‑term platform investments and allows them to align technology choices with evolving business strategies, regulatory landscapes, and IT modernization roadmaps.
Beyond the differentiators, every DPA vendor is expected to address a core set of use cases that form the foundation of digital process automation. These include business workflow automation, where repetitive, rule‑based sequences are streamlined across departments; department‑level and end‑user automation, which empowers individual teams and knowledge workers to automate their own routine tasks without heavy IT involvement; employee support agents, such as internal chatbots or virtual assistants that help staff navigate policies, request time off, or retrieve information; endpoint orchestration, which coordinates actions across diverse devices, applications, and IoT sensors to ensure timely responses; and incident and service request case management, a critical function for IT service desks, customer support centers, and public‑sector agencies that must track, prioritize, and resolve issues within defined SLAs. Mastery of these core capabilities indicates that a vendor possesses the fundamental orchestration engine, routing logic, and user‑interface components necessary to deliver reliable automation at scale. For organizations, verifying that a candidate platform covers these bases is a prudent first step before examining more specialized or industry‑specific extensions. It ensures that the platform can handle the day‑to‑day operational bread‑and‑butter while leaving room for advanced features like AI agents, adaptive orchestration, or industry‑tailored accelerators to be layered on top as needed.
Forrester invited each participating vendor to spotlight up to three extended use cases that represent areas of strategic focus beyond the core offerings. Newgen selected ‘AI agent industry outcomes, customer self‑service, and document automation’ as its focal points, a combination that reveals where the company believes it can deliver differentiated value. AI agent industry outcomes refers to the deployment of purpose‑built AI agents that are trained on sector‑specific data—such as loan underwriting patterns in banking, claims triage logic in insurance, or patient journey analytics in healthcare—to drive measurable business results like reduced processing times, improved decision accuracy, or enhanced regulatory reporting. Customer self‑service emphasizes empowering end‑users to initiate, track, and complete processes through intuitive portals, mobile apps, or conversational interfaces, thereby reducing reliance on call centers and increasing satisfaction scores. Document automation, meanwhile, tackles the pervasive challenge of handling unstructured information—extracting data from scanned forms, classifying contracts, routing invoices, and archiving records—using a blend of OCR, ML‑based classification, and intelligent workflow triggers. By highlighting these three areas, Newgen signals to prospects that its platform is not only capable of orchestrating generic processes but also of embedding deep, industry‑relevant intelligence that can transform front‑office interactions and back‑office document‑heavy operations. For buyers, mapping these extended use cases against their own pain points helps clarify whether Newgen’s strategic emphasis aligns with their priority initiatives.
Runki Goswami, CMO of Newgen Software, offered a reflective comment on the recognition, stating that ‘AI is redefining the enterprise, shifting the focus from automating individual tasks to orchestrating intelligence across the business. Organizations are increasingly looking for unified platforms that seamlessly connect processes, content, communications, and AI to drive faster decisions, operational resilience, and superior customer experiences.’ This statement captures the essence of the current market shift: the move from task‑level automation bots to a holistic intelligence layer where data flows, contextual awareness, and AI models coexist within a single orchestration framework. Goswami’s emphasis on ‘unified platforms’ echoes Forrester’s observation that vendors capable of integrating content management, business process management, and communication tools are better positioned to deliver the end‑to‑end visibility that decision‑makers crave. The mention of ‘operational resilience’ ties directly to the challenges of scaling AI projects—resilient systems can absorb integration hiccups, adapt to regulatory shifts, and maintain performance under varying loads. Finally, the reference to ‘superior customer experiences’ underscores the ultimate business outcome: when internal processes are orchestrated intelligently, external interactions become faster, more personalized, and less error‑prone. For readers, the quote serves as a reminder that technology investments should be evaluated not just on feature lists but on their ability to deliver tangible business outcomes that align with broader strategic goals such as agility, compliance, and customer centricity.
Forrester’s report also brings adaptive process orchestration (APO) into the spotlight, labeling it as DPA’s ‘top disruptor.’ APO represents an emerging approach where traditional, diagram‑based process design is supplanted by plain‑language agent instructions that describe desired outcomes rather than prescriptive step‑by‑step flows. In this model, business users or developers articulate goals—such as ‘approve a loan application if the applicant’s credit score exceeds a threshold and fraud risk is low’—and the underlying AI agent interprets the intent, consults relevant data sources, constructs a dynamic execution plan, and adapts that plan as conditions change. This shift mirrors the broader trend toward intent‑based computing and natural‑language programming, lowering the barrier to process creation while increasing the need for robust AI governance, explainability, and audit trails. Forrester anticipates that feature overlap between DPA and APO will grow as both markets mature, meaning that vendors will need to support both conventional workflow modeling and intent‑driven agent orchestration within a single platform. For organizations evaluating long‑term technology investments, this convergence suggests that locking into a solution that only supports static BPMN‑style diagrams could limit future agility. Instead, seeking platforms that offer hybrid capabilities—allowing users to switch between visual modeling and natural‑language authoring as needed—may provide a more resilient foundation for evolving process automation strategies.
The evolving relationship between DPA and APO underscores a broader market dynamic that procurement teams should factor into their platform selection criteria, not merely as a technical footnote but as a strategic consideration. As AI agents become more sophisticated and capable of interpreting complex business intent, the line between configuring a workflow and teaching an agent to achieve a goal continues to blur. Vendors that invest early in unifying these paradigms—offering, for example, a single authoring environment where a user can drag‑and‑drop BPMN elements or type a natural‑language command and have the system translate it into an executable process—are likely to enjoy a competitive advantage. Moreover, the rise of APO highlights the growing importance of AI explainability, version control, and auditability, especially in regulated sectors where every automated decision must be traceable to a clear rationale. Organizations should therefore assess whether a prospective vendor provides transparent logging of agent decisions, easy rollback mechanisms, and compliance‑ready reporting features. Additionally, the increasing overlap suggests that investments made today in DPA capabilities that also support APO‑style interactions will retain relevance longer, protecting the organization from premature obsolescence. In practice, this means looking for platforms that showcase strong AI model management, robust integration frameworks, and clear roadmaps for advancing both traditional workflow and intent‑based orchestration.
For enterprises navigating the complex landscape of digital process automation, the Forrester Q3 2026 report and Newgen’s recognition within it offer several actionable insights. First, prioritize vendors that demonstrate a proven ability to deliver end‑to‑end automation rather than isolated task bots; look for case studies that show measurable improvements across entire value chains, from intake to fulfillment. Second, evaluate the vendor’s deployment flexibility—ensure they can support hosted/private SaaS, multitenant SaaS, and on‑premises models so you can align the solution with your data‑governance and infrastructure requirements now and in the future. Third, scrutinize how the platform incorporates AI agents: ask for details on model training data, explainability tools, governance controls, and success metrics in industry‑specific scenarios such as underwriting, claims processing, or patient intake. Fourth, consider the vendor’s extended use‑case focus; if your organization’s pain points center on customer self‑service, document‑heavy processes, or sector‑specific AI outcomes, a provider highlighting those areas may deliver faster relevance. Fifth, keep an eye on the emerging adaptive process orchestration trend; favor platforms that either already support intent‑based authoring or have a clear roadmap to converge traditional workflow modeling with natural‑language agent instructions. Finally, treat the selection process as a continuous evaluation: establish success criteria tied to business outcomes like cycle‑time reduction, compliance audit scores, and customer satisfaction, and revisit them regularly as both your needs and the technology evolve. By following these guidelines, decision‑makers can move beyond hype and invest in a DPA platform that drives genuine, sustainable transformation.