Newgen Software’s recent inclusion among the Notable Vendors in Forrester’s Digital Process Automation Software Landscape for Q3 2026 marks more than a routine accolade; it reflects a broader industry pivot toward platforms that treat automation as a strategic, enterprise‑wide capability rather than a collection of isolated scripts. In an era where artificial intelligence is moving from experimental pilots to core operational fabric, analysts are asking which vendors can truly deliver the promise of end‑to‑end process intelligence while respecting the complex realities of legacy systems, regulatory oversight, and human‑centric workflows. Newgen’s positioning in the report highlights its ability to stitch together content, process, and communication layers into a unified orchestration engine, a capability that many organizations now deem essential for achieving resilience and agility. This recognition arrives at a moment when decision‑makers are reevaluating their automation roadmaps, seeking proof points that a platform can scale beyond departmental pilots to become the nervous system of the entire enterprise. For technology leaders, the acknowledgement serves as a signal to examine how Newgen’s approach aligns with their own transformation goals, especially in sectors where compliance and case‑management depth are non‑negotiable. The accolade also underscores the importance of vendor transparency in reporting capabilities, as Forrester’s landscape relies on self‑disclosed data complemented by analyst validation, giving buyers a credible baseline for comparison. Moreover, the recognition invites stakeholders to look beyond the badge and evaluate how the vendor’s roadmap addresses emerging trends such as agentic execution and adaptive process orchestration, which are poised to reshape the competitive landscape over the next 24‑36 months.
The Forrester Landscape report casts a wide net over the digital process automation market, examining 39 vendors that claim to deliver platforms capable of building process applications through advanced programming principles, visual modeling, dynamic case management, and AI‑led support. According to the analyst firm, DPA is not merely about routing tasks from one system to another; it is about enabling organizations to encode business logic, data flows, and human interactions into a cohesive environment where changes can be propagated swiftly and safely. The report emphasizes that modern DPA solutions must support low‑code or no‑code development while still offering the depth required for complex, regulated workflows. By evaluating vendors across dimensions such as geographic reach, industry focus, deployment options, and extended use‑case prioritization, Forrester aims to give procurement teams a multidimensional view that goes beyond feature checklists. This holistic perspective is particularly valuable as buyers confront a proliferating ecosystem where the lines between traditional workflow tools, robotic process automation, and AI‑driven decision engines continue to blur. Understanding where a vendor sits within this matrix helps organizations anticipate integration effort, total cost of ownership, and the ability to evolve the platform as business needs shift. Consequently, the Landscape serves as both a benchmark and a compass for those seeking to invest in automation technology that can deliver sustained value rather than short‑term gains.
The report highlights a growing ‘automation imperative’ fueled by optimism around artificial intelligence, with a striking 54 percent of automation decision‑makers indicating that their organizations need to shift focus from piecemeal workflow and task automation toward comprehensive end‑to‑end process coverage. This statistic reveals a maturation in buyer mindset: rather than celebrating isolated efficiency gains, enterprises are now demanding that automation initiatives deliver measurable outcomes across the full lifecycle of a business process, from intake and validation to fulfillment and post‑execution analytics. The shift is driven by pressure to improve customer experience, reduce operational risk, and unlock hidden capacity in knowledge‑intensive functions such as underwriting, claims adjudication, and regulatory reporting. When automation is confined to discrete tasks, the benefits often evaporate at handoff points where manual interventions reintroduce delay, error, and compliance gaps. By contrast, end‑to‑end automation promises seamless data flow, consistent governance, and the ability to apply AI insights at every stage, thereby amplifying return on investment. For vendors, the challenge lies in demonstrating that their platforms can orchestrate heterogeneous systems, manage state across long‑running cases, and provide the transparency needed for audit trails—all while remaining accessible to business analysts who may not possess deep coding expertise.
Forrester identifies agentic execution as the market’s dominant trend, describing AI agents that dynamically construct work patterns based on real‑time context and evolving conditions, thereby augmenting rather than replacing static workflow definitions. Unlike traditional rule‑based engines that follow pre‑drawn flowcharts, agentic systems observe data streams, user behavior, and external signals to infer the most appropriate next steps, learning from each iteration to refine future decisions. This approach enables processes to adapt to exceptions without requiring explicit redesign, a valuable attribute in environments where regulatory guidance, market conditions, or customer preferences shift frequently. For example, an AI agent in a loan‑origination workflow might detect anomalous credit signals, automatically request supplemental documentation, and route the case to a specialized underwriter, all while logging the rationale for auditors. The promise of agentic execution lies in its ability to bridge the gap between deterministic automation and human judgement, offering a scalable way to embed intelligence into routine operations. However, realizing this promise demands robust data foundations, model governance frameworks, and clear escalation paths to human operators when confidence thresholds are not met. Vendors that can deliver trustworthy, explainable agentic capabilities are likely to gain a competitive edge as organizations seek automation that feels less like a rigid script and more like a responsive partner.
The report also flags a primary obstacle that many enterprises encounter when attempting to move AI‑embedded automation projects from pilot to production: the difficulty of scaling without stumbling into multisystem integration gaps, human‑interaction breakdowns, or regulatory compliance issues. Pilot projects often succeed in isolated sandboxes where data sources are limited, stakeholder groups are small, and regulatory scrutiny is minimal. When the same solution is expanded across business units, geographic regions, or legacy platforms, inconsistencies in data schemas, authentication mechanisms, and interface standards can create friction that erodes the anticipated efficiency gains. Furthermore, as automation touches more human‑centric touchpoints—such as customer service portals or approval workflows—the risk of misaligned expectations, insufficient training, or change‑resistance rises sharply. On the compliance front, regulations governing data privacy, financial reporting, or industry‑specific mandates frequently require detailed audit trails, consent management, and the ability to demonstrate that automated decisions adhere to established rules. Vendors that address these scaling challenges by offering built‑in adapters, comprehensive API management, and configurable governance controls are better positioned to help customers transition from proof‑of‑concept to enterprise‑wide deployment without costly rework.
For prospects evaluating DPA vendors, the Landscape provides a useful lens into where Newgen fits, noting its geographic focus across North America, EMEA, and APAC, and its industry emphasis on financial services and insurance, government and public sector, and healthcare. These three sectors share common characteristics that make them fertile ground for sophisticated process automation: high levels of regulatory scrutiny, extensive reliance on case‑management workflows, and a persistent need to handle large volumes of structured and unstructured documents. In banking, for instance, automation must accommodate know‑your‑customer (KYC) checks, anti‑money‑laundering (AML) monitoring, and loan servicing while maintaining immutable records for regulators. Government agencies often manage complex benefit eligibility determinations, permit issuance, and public records requests that span multiple departments and legacy systems. Healthcare providers face similar pressures with patient intake, claims adjudication, and clinical documentation improvement, all of which demand strict adherence to HIPAA and other privacy frameworks. By concentrating its go‑to‑market efforts on these verticals, Newgen can tailor its solution accelerators, compliance templates, and industry‑specific AI models to address the precise pain points that impede operational efficiency in regulated environments.
Another differentiator highlighted in the report is Newgen’s support for all three primary deployment models tracked by Forrester: hosted/private SaaS, multitenant SaaS, and on‑premises installations. This flexibility matters profoundly for organizations operating under stringent data sovereignty, residency, or latency requirements, where a single‑architecture mandate could impede adoption or trigger costly workarounds. A hosted private SaaS offering enables enterprises to reap the benefits of cloud‑based elasticity—such as automatic scaling, continuous updates, and reduced infrastructure overhead—while retaining logical isolation and dedicated resources that satisfy internal audit or corporate governance policies. Multitenant SaaS, on the other hand, delivers rapid time‑to‑value and lower total cost of ownership for use cases where data sensitivity permits shared tenancy, making it ideal for departmental pilots or global rollouts that benefit from a common code base. Finally, on‑premises deployment remains essential for industries where data cannot leave the premises due to legal restrictions, or where existing investments in hardware and network architecture necessitate a localized installation. By providing a genuine choice among these models, Newgen empowers customers to align their automation strategy with IT policy, risk tolerance, and long‑term roadmap without being forced into a compromising architecture that could limit future innovation.
Beyond the vendor‑specific nuances, every DPA participant is expected to address a set of core use cases that form the foundation of process automation capability. These include business workflow automation, department and end‑user automation, employee support agents, endpoint orchestration, and incident and service request case management. Business workflow automation covers the end‑to‑end coordination of activities across systems, ensuring that tasks are triggered, routed, and completed according to predefined logic while allowing for dynamic exceptions. Department and end‑user automation focuses on empowering line‑of‑business teams to build and modify their own processes through intuitive low‑code interfaces, reducing reliance on central IT for routine improvements. Employee support agents leverage conversational AI to provide instant answers to HR, IT, or policy questions, thereby decreasing ticket volume and improving employee experience. Endpoint orchestration extends automation to the edges of the network—such as desktop applications, mobile devices, or IoT gateways—enabling actions like data capture, device configuration, or real‑time alerts to be triggered from process flows. Incident and service request case management brings together ticketing, knowledge bases, and SLA tracking into a unified framework that allows organizations to resolve issues efficiently while maintaining visibility for continuous improvement. Mastery of these core areas indicates that a vendor possesses the fundamental building blocks required to support a wide spectrum of automation initiatives, from simple task routing to complex, long‑running cases.
Forrester asked each participating vendor to identify up to three extended use cases that represent areas of strategic focus, and Newgen selected ‘AI agent industry outcomes, customer self‑service, and document automation.’ This selection reflects a deliberate emphasis on extending the value of automation beyond process orchestration into domains where AI can generate measurable business results. AI agent industry outcomes point to the deployment of specialized agents that are trained on sector‑specific data—such as credit risk models for banking or fraud detection patterns for insurance—to drive decisions that directly impact revenue, cost, or risk profiles. Customer self‑service highlights the growing expectation that end users should be able to initiate, track, and complete interactions—such as opening an account, submitting a claim, or updating personal information—through intuitive digital channels without needing to contact a call center. By embedding self‑service portals within the orchestration layer, organizations can reduce friction, improve satisfaction, and free up human agents for higher‑value tasks. Document automation remains a critical enabler in industries where contracts, forms, and supporting evidence constitute a large share of the workload; capabilities such as intelligent capture, classification, extraction, and automated routing help eliminate manual data entry, accelerate turnaround times, and enhance accuracy. Together, these three focus areas illustrate how Newgen envisions its platform as a catalyst for outcomes that matter to the bottom line while also improving the experience of both employees and customers.
The reaction from Runki Goswami, CMO of Newgen Software, offers additional insight into how the company interprets its recognition and the broader market direction. Goswami notes that AI is redefining the enterprise by shifting the focus from automating individual tasks to orchestrating intelligence across the business, a sentiment that aligns with Forrester’s observation about the rise of agentic execution and adaptive process orchestration. She emphasizes that organizations are increasingly seeking unified platforms capable of connecting processes, content, communications, and AI to drive faster decisions, operational resilience, and superior customer experiences. This perspective underscores the importance of treating automation not as a disparate set of tools but as an integrated operating model where data, workflows, and intelligent agents coexist under a common governance framework. Goswami’s statement also reflects confidence that Newgen’s vision of orchestrating intelligent enterprises resonates with analyst assessments, reinforcing the idea that the vendor’s product roadmap is aligned with where the market is heading. For customers, such leadership commentary can serve as a cue to evaluate whether the vendor’s strategic narrative matches their own transformation objectives, particularly in areas like AI‑driven decision making, cross‑system data harmony, and the ability to evolve the platform as new technologies emerge.
The report also alerts readers to a market dynamic worth watching: adaptive process orchestration (APO), which Forrester labels the top disruptor to traditional DPA, is emerging to directly challenge conventional orchestration logic by allowing visual process design to be authored as plain‑language agent instructions rather than rigid flowcharts. This shift suggests that the future of process modeling may lean toward natural‑language descriptions that are interpreted by AI agents into executable workflows, thereby lowering the barrier for business users to create and modify processes while still maintaining the precision required for automation. As APO matures, feature overlap between DPA and APO is expected to increase, meaning that platforms historically categorized under one label may begin to offer capabilities traditionally associated with the other. For enterprises evaluating long‑term platform investments, this convergence implies that locking into a vendor based solely on today’s DPA feature set could limit flexibility when APO‑style capabilities become table stakes. Decision‑makers should therefore inquire about a vendor’s roadmap for natural‑language process authoring, model‑driven execution, and the ability to import or export processes between DPA and APO environments. By factoring the evolving relationship between these adjacent categories into their selection criteria, organizations can hedge against obsolescence and ensure that their chosen platform remains capable of supporting both current workflow needs and emerging AI‑centric automation paradigms.
For technology leaders and process owners who are actively assessing digital process automation vendors, the insights from Forrester’s Q3 2026 Landscape provide a concrete framework for making informed, future‑ready decisions. Begin by mapping your organization’s most pressing automation goals—whether they center on reducing manual effort in high‑volume transactions, enhancing compliance auditability, or delivering seamless omni‑channel customer experiences—against the vendor’s stated industry focus, geographic coverage, and deployment flexibility. Prioritize vendors that demonstrate proven ability to scale AI‑embedded solutions from pilot to production, offering concrete examples of how they have addressed integration gaps, human‑interaction challenges, and regulatory demands in real‑world implementations. Examine the vendor’s stance on emerging trends such as agentic execution and adaptive process orchestration; request demonstrations or proof‑of‑concepts that showcase natural‑language process authoring, explainable AI decisions, and smooth hand‑offs between automated and human steps. Finally, consider the total cost of ownership, not just licensing fees but also the effort required for training, change management, and ongoing governance, and ensure that the vendor’s support model aligns with your internal capabilities. By following these steps, you can select a DPA platform that not only satisfies today’s requirements but also positions your enterprise to harness the next wave of intelligent, adaptive automation.