Full-Time

Enterprise Architecture Principal Analyst

Forrester

Forrester

1,001-5,000 employees

Subscription-based market research and advisory

No salary listed

United Kingdom

Hybrid

Category
IT & Security (1)
Required Skills
Operating Systems
Risk Management

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Requirements
  • Experience in a mix of roles as a director-level and above practitioner, enterprise architect, principal sales engineer, principal solutions architect, managing consultant, Director/Manager of Sales Engineering, or research analyst in an industry vertical or technology services.
  • Demonstrated ability to serve as an advisor to senior management and C-level clients.
  • Superior client-facing communication, listening, critical thinking, and collaboration skills with researchers, subject-matter experts, and client leaders.
  • Solid technical enterprise architecture, the practice, solutions architecture and technology experiences as a leader but also founded in engineering and architecture backgrounds in key platforms. These platforms can include Cloud, Infrastructure, AI, Operating Systems, Security as well as additional technology platforms.
  • Practitioner experiences in Financial Services, Technology Services or another key industry vertical is preferred, including the ability to craft high-level architecture to illustrate complex topics and research coverage.
  • Ability to leverage prevailing AI topics and technologies as they relate to the practice of Enterprise Architecture as well as AI tools and solutions architecture.
  • Ability to engage technology leaders across Enterprise Architecture, IT Delivery and Operations.
  • Strong knowledge of the issues and challenges that technology executives and leaders face and expertise in the broad implications of current and emerging technology markets, economics, labor, and econometrics.
  • Ability to take complex, disparate ideas and distill them into simple, provocative concepts; willingness to take a stand on outcomes with clients, vendors, press, and competition.
  • A strong record of academic achievement.
  • Superior analytical, writing, editing, and presentation skills.
  • The ability to travel 30% of the time or more.
Responsibilities
  • Lead the Enterprise Solutions Architecture practice area, working across Forrester research teams, including Technology Strategy and Executive Partner teams as well as Sales and Product to develop a complete research portfolio that drives customer delight and revenue.
  • Develop a deep understanding of what Forrester clients require to be successful as technology executives and leaders.
  • Establish an industry presence as an influential speaker and thinker; build relationships with journalists who cover the sector; participate in vendor briefings and field press inquiries as necessary.
  • Conduct primary research into architecture strategy, solutions architecture, key technology platforms, and roadmaps; governance and risk management; financial and cost optimization; and performance management including metrics, KPIs, benchmarks etc. Use this research to help clients navigate challenges by providing insights on the future of solutions architecture, cost optimization, investment prioritization, and long-term workplace strategy.
  • Conduct deep analysis of IT decision maker challenges and preferences balanced with employee preferences and expectations.
  • Create high quality, actionable, analytically deep and fact-based research content throughout the year. Research/write/create approximately 8 to 12 research projects per year, which includes mix of written reports, tools, webinars, videos, blogs, podcasts, infographics, and other intellectual property. Build visibility for his/her research and contribute to Forrester client communities.
  • Drive and lead key Forrester Waves and Landscape reporting for the practice and adjacent areas.
  • Consult with clients to apply Forrester’s research in the context of their specific business environment and help solve their problems through inquiry, guidance, and advisory and consulting engagements.
  • Present at Forrester-sponsored and industry-related events and deliver client webinars.
  • Co-lead the global Forrester Enterprise Architecture forum and award program.
  • Contribute to the State of Modern Technology Operations survey, a key adjacent area.
  • Support business development and prospect conversations as arranged by Forrester’s account leadership teams.
  • Foster a leadership style that drives a culture of cross-team collaboration, mentorship, integrity and relentless & positive pursuits.
  • This role can grow into the VP Principal Analyst role for a very driven individual that brings new innovations to Forrester and to our clients as well as capture revenue and client engagement.

Forrester provides global market research and advisory services to business and technology leaders. Its flagship Forrester Decisions subscription gives ongoing access to research reports, data, and advisory support, while revenue also comes from consulting, events, and custom projects. The company blends wide-market research with continuous advisory services and events, focusing on customer obsession and diverse perspectives. Its goal is to help clients grow by making customer-centered decisions across products, channels, and technology-enabled experiences.

Company Size

1,001-5,000

Company Stage

IPO

Headquarters

Cambridge, Massachusetts

Founded

1983

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Simplify Jobs

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What believers are saying

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  • Forrester’s credibility as an independent advisor is reinforced by its focus on AI transformation and human-AI integration strategies. Its holistic model strengthens value in customer obsession and workforce planning amid growing AI adoption. The firm’s research addresses the credibility gap in AI-driven layoffs, adding strategic value to clients.
  • Forrester’s new Employee Experience Index enables clients to measure employee engagement’s impact on CX and AI outcomes. This holistic approach supports its authority in enterprise adoption trends and AI productivity. The firm’s advisory value remains relevant as agentic AI reshapes modern work.

What critics are saying

  • Forrester is exiting strategy consulting, causing a 13% revenue drop in that segment, with total revenue projected to decline 9.3–11.8% in 2026. GAAP operating margin is expected to turn negative (–2.8% to –3.3%) within 6–12 months, posing high-impact financial risk.
  • Competitor Salesforce is now ranked as a Leader in B2B Revenue Marketing Platforms by Forrester’s own 2026 study, potentially eroding Forrester’s credibility as an independent advisor. This could enable Salesforce to capture enterprise clients Forrester previously influenced, with medium impact in 6–12 months.
  • Forrester’s AI agent for Copilot, launched at no cost, may devalue its subscription research portfolio by embedding insights so deeply clients perceive less need for standalone access. This could accelerate churn within 12–18 months, with medium impact. Contract value declined 3% in Q1 2026, raising liquidity concerns.

What makes Forrester unique

  • Forrester is the only research firm with AI integrations across Microsoft Teams and Copilot. It launched the first industry AI agent for Microsoft 365 Copilot at no extra cost for existing license holders. Forrester embeds its proprietary insights and frameworks into Copilot, enabling real-time action by clients.
  • Forrester’s new Employee Experience Index complements its Total Experience Score, quantifying employee impact on CX and AI outcomes. It emphasizes customer obsession as a core driver of growth and innovation across its research and advisory services. The firm serves 57% of Fortune 100 companies, reinforcing its strategic influence and market reach.
  • Forrester warns that 9 out of 10 companies lack AI readiness to replace workers, highlighting a credibility gap in AI-driven layoffs. Its research and tools help leaders navigate the shift toward operational AI maturity and agentic automation. The firm publishes authoritative studies like 'The Total Economic Impact of Microsoft 365 Copilot'.

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TechNovice
Jul 10th, 2026
Business-Ready Data: Why AI only works with clean data.

Business-Ready Data: Why AI only works with clean data. Key takeaway in one sentence: Gartner predicts that by 2026, around 60 percent of all AI projects will be abandoned - not because of poor models, but because of a lack of AI-ready data. A Forrester TEI study commissioned by Syniti and SAP shows what companies can specifically achieve with "business-ready data." In short (TL;DR). * The problem: Fragmented systems, duplicate data sets, and inconsistent formats prevent reliable AI results. * The number that counts: According to Gartner, 60% of all AI projects will be stopped by 2026 due to a lack of AI-compatible data. * The proof: Forrester TEI study on SAP ADMM users shows 218% ROI, $4.1 million in realized benefits, amortization in under 6 months. * The key: Automation reduces data management effort by ~30%, audit preparation by 80%. * The context: In one case, data compliance increased from ~45% to almost 99% after the introduction of structured data processes. What does "business-ready data" actually mean? Business-ready data refers to data that is reliable, consistent, and prepared in such a way that it can be used directly for business decisions and AI applications. The term deliberately distinguishes itself from mere "data quality": it's not just about data being correct, but about it being in a state that an AI system can use productively without manual intervention. For years, companies have been investing in data transformation to optimize processes and reduce costs. With the AI boom, this investment takes on a new strategic dimension: it is a prerequisite for AI projects to become productive in the first place. Gartner's warning: 60 percent of AI projects are on the verge of collapse. Gartner is issuing a stark warning to companies that are rushing their AI initiatives: By 2026, 60 percent of all AI projects are expected to be abandoned because they are not based on AI-compatible data. This is the key figure in this article - and it shows that the bottleneck for successful AI implementation is rarely the model itself, but almost always the data that feeds it. As companies move from initial AI experiments to enterprise-wide deployment, data quality, consistency, and governance become crucial success factors. The added value of even the most powerful models is ultimately limited by the quality of the underlying data. What the Forrester TEI study specifically shows. The Total Economic Impact(TM)(TEI) study by Forrester Consulting, commissioned by Syniti and SAP, examines companies that use SAP solutions for their data transformation. Key findings: | Key figure | Result | | ROI | 218% | | Realized benefits | USD 4.1 million | | Payback period | under 6 months | | Reduction of data management effort | ~30% | | Audit preparation reduction | 80% | | Data compliance (case study) | from ~45% to ~99% | Beyond the pure cost advantages, the surveyed companies report higher productivity, greater employee responsibility, better organizational agility and optimized cross-departmental collaboration. Without data quality, there can be no successful use of AI. Many companies continue to struggle with fragmented systems, duplicate data sets, and inconsistent formats. The result: data sets that are only partially usable or not usable at all. Previously, this primarily led to business risks. Today, it directly jeopardizes the success of AI initiatives: Poor data quality means inaccurate results, unreliable recommendations, and declining trust in AI-generated insights. Automation as an accelerator. The greatest effort before productive use of AI often lies in data preparation: cleaning, validation, reconciliation, documentation - done manually, this ties up enormous resources. According to a TEI study, increased automation and standardization reduces this time expenditure by approximately 30 percent. Replacing fragmented processes with integrated workflows significantly shortens the path from initial pilot projects to productive AI deployment. Governance and accountability: not a nice-to-have. With increasing AI integration into business processes, consistent data governance becomes a basic requirement - transparency about data origin and processing, as well as compliance with guidelines throughout the entire lifecycle. The TEI study shows how automated workflows, audit trails, and greater transparency in data origin, approvals, mappings, and transformation processes improve governance. One highlight: 80 percent less effort for audit preparation. Scalable innovation instead of individual projects. The success of AI rarely hinges on a single project. Long-term added value arises when innovations can be scaled across business areas, functions, and use cases. Companies that have centralized and standardized their data report improvements in reporting, forecasting, and decision-making - and can implement future transformation projects without rebuilding data structures each time. The same logic applies to AI: professionally managed data facilitates the scaling of AI initiatives. Conclusion: Data transformation is the real competitive advantage. Sustainable competitive advantages in the AI age arise not only from powerful algorithms, but also from the quality and trustworthiness of the underlying data. The Forrester TEI study confirms that data transformation creates the foundation for governance, consistency, and data quality - and thus for scalable AI applications. Companies that consistently modernize and professionally manage their data will have a distinct advantage. Frequently asked questions (FAQ). What does "business-ready data" mean? Data that is so reliable, consistent, and processed that it can be used directly for business decisions and AI applications without manual rework. According to Gartner, how many AI projects fail due to a lack of data? Gartner predicts that by 2026 around 60 percent of all AI projects will be discontinued because they lack AI-compatible data. What ROI does the Forrester TEI study show for Business-Ready Data? According to the study, companies using SAP ADMM achieved an ROI of 218 percent, realized benefits of 4.1 million US dollars and a payback period of less than six months. How much does automation reduce the effort required for data management? According to the companies surveyed in the study, the savings amount to around 30 percent for ongoing data management activities and 80 percent for audit preparation. Why is data governance so important for AI projects? Because AI systems are only as trustworthy as the data they are based on. Governance ensures transparency regarding data origin and processing and helps to meet regulatory requirements.

Forrester
Apr 10th, 2026
IBM and the converging forces reshaping enterprise AI.

IBM and the converging forces reshaping enterprise AI. Apr 10 2026 Forrester Research, Inc. attended IBM's APAC Analysts Insights event in Bangalore this week. The event surfaced a thesis worth examining: digital sovereignty, the rise of agentic AI, and cybersecurity are converging in ways that favor vendors with broad, integrated stacks. IBM is making an aggressive play across all three. Here's what tech leaders should take away - and where the open questions remain. Digital sovereignty is IBM's structural tailwind. Digital sovereignty has moved from a European regulatory conversation to a global strategic imperative. Across Asia Pacific, governments and enterprises are demanding control. Not just over where data sits, but over who technically operates the platform, who holds the keys, and who can produce compliance evidence on demand. Critically, sovereignty requirements must hold across hybrid architectures - on-prem, private cloud, and public cloud. This raises the bar for any vendor claiming sovereign capabilities. IBM's answer is Sovereign Core: an open-source-based, customer-operated framework designed to transfer full control from IBM to the client or a local operator, running on any infrastructure footprint. IBM believes that its open-source focused acquisition strategy strengthens this positioning. Red Hat anchors IBM in the open-source communities that sovereignty-minded governments trust. Confluent's Kafka provides event-driven data streaming across hybrid environments, with over 1,000 pre-built connectors into SAP, Oracle, and other enterprise systems. DataStax adds distributed data capabilities through Cassandra. IBM's believes that this stack can enforce sovereignty requirements end to end, not just at the infrastructure layer. Tech leaders evaluating sovereignty options should start with Forrester's minimum viable sovereignty framework, a risk-based approach that identifies which workloads genuinely require sovereign controls and which do not. Context engineering is the real battleground. As enterprises scale agentic AI - deploying autonomous agents that reason, retrieve, and act on enterprise data -a new bottleneck emerges: context engineering. Agents are only as effective as the semantic and ontological layers that connect them to enterprise knowledge. Only 25% of enterprises are seeing AI impact today, and the gap is not model capability but accumulated context debt: fragmented data estates, inconsistent taxonomies, and data infrastructure designed for human dashboards, not autonomous agents. IBM is investing in the context layers that it argues make agentic AI operationally viable. Its composable data platform (built on open formats) feeds a context layer that ships as reusable skills, tools, and MCPs consumable by any agent platform. The design orientation is explicit: "APIs are our new users, agents are our new customers." This is an open-ecosystem play: IBM positions itself as a context infrastructure provider regardless of which agent framework the client adopts. Security completes the sovereignty-to-agentic arc. IBM's cybersecurity leadership presented two reinforcing arguments. First, security for AI: every agent in production needs testing, governance, and continuous monitoring - yet only roughly 25% of AI initiatives adequately address both functionality and security. As enterprises deploy agents with elevated permissions and autonomous decision authority, the attack surface expands accordingly. Second, AI for security: agentic SOCs that compress P1/P2 response times from hours to minutes through orchestrated, specialized agents (like threat intelligence, asset analysis, or anomaly detection) dynamically assigned based on incident context. IBM indicated that the timeline for autonomous security operations has accelerated materially, with capabilities originally forecast for 2027-2028 arriving now. For CIOs, the security thread reinforces a principle that applies regardless of vendor: governance and compliance in an agentic world must be continuously enforced through policy-as-code and embedded controls, not static audits. Forrester's AEGIS framework - purpose-built for securing agentic AI across six domains from identity management to threat operations - provides the evaluation lens CISOs should apply here. IBM's alignment of this philosophy across Sovereign Core and its security portfolio is architecturally consistent, though CIOs should evaluate how these capabilities compare to competing approaches. The convergence test. Tech leaders should watch this space closely. The converging forces IBM is responding to - sovereignty, agentic AI and cybersecurity - are real and affect every enterprise. IBM's positioning against them is more clear than it has been in years. Whether that clarity translates into client outcomes at scale is what will matter in the long term.

Forrester
Apr 3rd, 2026
Meet Jess Lloyd: Forrester's new principal analyst covering consumer behavior.

Meet Jess Lloyd: Forrester's new principal analyst covering consumer behavior. Apr 3 2026 Consumers don't stand still. And neither can the companies trying to reach them. Attitudes shift, expectations evolve, and new behaviors emerge faster than most organizations can track. That's why Forrester invests so heavily in understanding consumers in real time. One of the things I love most about Forrester is the sheer depth and breadth of its consumer data. From its massive annual Consumer Benchmark Survey to topic-based work such as media and technology, Forrester Research, Inc. is constantly tracking how consumers think, feel, and behave. Its monthly Consumer Pulse Surveys help Forrester Research, Inc. monitor change as it happens. And when breaking news hits, Forrester's ConsumerVoices online panel lets Forrester Research, Inc. gather polling data and qualitative verbatims in a matter of hours. This data advantage is foundational to how Forrester Research, Inc. help clients understand consumers - not as static personas but as humans responding to the fury of constant change. Human truth is at the heart of marketing. Especially in the age of AI, understanding rapidly evolving consumer behavior isn't optional. B2C marketing leaders need a clear, evidence-based view of what's changing, why it matters, and how to respond. Its portfolio of consumer insights research spans everything from technology usage, immersive tech, US youth, trust in AI, gaming, podcasts, streaming services, global trust, and more. And beyond its published research, Forrester clients can always request data guidance sessions for custom cuts - going deeper into the questions that matter most to their business. Welcome to Forrester: Jess Lloyd. While many Forrester analysts leverage its consumer data, its consumer behavior analyst plays a unique role: serving as the anchor and guide for business leaders trying to make sense of the forces shaping consumer expectations, purchase decisions, and brand relationships. That's why I'm thrilled to welcome back to Forrester Jess Lloyd. The one constant is change - and that's never truer than when it comes to the consumer. Jess brings deep practitioner experience across marketing strategy, consumer insights, and brand planning. She joins Forrester Research, Inc. from Hill Holliday, where she led the agency's strategy practice as EVP and head of strategy - helping brands across healthcare, financial services, and education turn consumer insights into differentiated growth strategies. Before that, Jess led strategy at DiMassimo Goldstein, where she built and scaled capabilities across customer research, journey mapping, brand strategy, and integrated communications - including leading a record-setting CPG product launch. Earlier in her career, as a principal consultant at Slalom, she helped clients across biotech, retail, and financial services connect brand strategy and consumer insights to broader business decisions. At Forrester, Jess helps companies adopt customer-obsessed ways of working by aligning teams, processes, and planning frameworks around a shared understanding of the consumer. That includes equipping CMOs with a clear view of macro consumer trends and arming customer insights professionals with practical frameworks and best practices to advance their top infinitives. See Jess speak AT CX Forum in June. Check out the video above to learn more about Jess and see her keynote at Forrester's CX Forum East (June 16-17) or CX Forum West (June 29-30). And if you're a Forrester client, you can request a Forrester guidance session with her starting today. See mike proulx at: CX Forum East June 16-17, 2026, New York City CX Forum West June 29-30, 2026, San Francisco Cut through CX tech noise and buy smarter. As AI absorbs execution at scale, creativity returns to its highest value. The brands that win will automate production while doubling down on insight, narrative, and the judgment that protects meaning. Milestone anniversaries invite reflection when what's required is foresight. Apple is at a crossroad - and the way forward may require challenging some of the very principles that have made it so successful.

CommerceNext
Apr 3rd, 2026
2026 digital retail forecast: challenges, opportunities and strategies.

2026 digital retail forecast: challenges, opportunities and strategies. * Session Recaps Register for the 2026 CommerceNext Growth Show, June 23-24 in NYC to join 2700+ attendees, 150+ speakers and 60+ sessions. Economic uncertainty, fragmented discovery, shifting generational behavior and rising expectations around trust are all reshaping how retailers plan for growth. In this CommerceNext webinar, Forrester, Mejuri, B&H Photo and RTB House came together to explore what digital retail leaders need to know about 2026 and how brands can adapt without losing sight of the fundamentals. What CommerceNext, LLC covered: * Peak ambiguity and the new planning environment * Discovery is fragmenting, but proven channels still matter * Consumer behavior is more research-heavy, generational and multi-device * Trust, fulfillment and measurement will define the winners Speakers: * Sucharita Kodali, VP & Principal Analyst, Forrester * Rohit Nathany, CTPO, Mejuri * Jeff Gerstel, CMO, B&H Photo * Jaysen Gillespie, VP, Global Head of Product Marketing and Analytics, RTB House * Moderated by: Jenny Marlo, Head of Content, CommerceNext Peak ambiguity and the new planning environment. Forrester framed 2026 with a phrase that set the tone for the entire conversation: peak ambiguity. Between high interest rates, soft consumer sentiment, geopolitical volatility and ongoing questions around AI's impact on jobs, creativity and decision-making, retail leaders are operating in an environment where certainty is in short supply. The panel reinforced that there is no single playbook for how adjusting to this ambiguity. Mejuri explained that for growing brands like themselves, the answer is not to retreat but to focus on sustainable growth, scenario planning and the fundamentals that matter most: strengthening the brand, investing in customer experience and building community. B&H Photo offered a similarly pragmatic view, emphasizing the importance of focusing on what you can control, staying flexible and continuing to execute against what already works while remaining ready for sudden change. 2026 planning cannot be passive. Retailers need to actively plan around softer demand, operational pressure and uneven market conditions, even if the exact shape of disruption is still unfolding. Discovery is fragmenting, but proven channels still matter. The "front door" to retail is getting more crowded. Search is no longer the only place discovery begins. Social platforms, AI tools and answer engines are increasingly entering the mix, especially for younger consumers. But that does not mean retailers should rush to abandon the channels that already perform. Forrester described this shift as discovery disrupted. Google remains dominant, but consumers are also turning to Instagram, TikTok and AI tools like ChatGPT for product discovery and research. Much of that activity is still top-of-funnel, focused on research, comparison and summaries rather than transactions. Forrester also noted that even if AI could make purchasing faster than Amazon, 80% of consumers would still prefer to complete their purchase through Amazon. B&H Photo emphasized a measured approach, testing emerging platforms without pulling spend from proven channels. Discovery is evolving, but not fully transformed, so brands should keep experimenting while staying disciplined on performance. Mejuri noted that AI-driven discovery will vary by category, especially in highly visual spaces like jewelry. Still, the brand is reinforcing the importance of core fundamentals like community, UGC and strong brand presence, with added focus on monitoring how brands surface in AI search. The takeaway: discovery is widening, not replacing. Retailers should test new platforms, but protect the channels that still drive meaningful performance. Consumer behavior is more research-heavy, generational and multi-device. RTB House's research added a sharp consumer lens to the webinar and challenged some familiar assumptions about how people shop online today. One of the most striking findings was that even relatively low-cost purchases often require multiple site visits before conversion. For higher-ticket products, that consideration cycle becomes even longer, with many shoppers returning four, five or six times before they are ready to buy. This behavior is especially pronounced among younger consumers. Gen Z and Millennials are more likely to research extensively, spend longer evaluating options and leave products sitting in their cart for days before checking out. By contrast, older shoppers are more likely to arrive knowing what they want and complete the purchase in fewer steps. RTB House argued that these younger behaviors are not a passing phase. They are likely to shape the future of commerce more broadly. The research also reflected a more price-conscious consumer environment. Shoppers are still switching retailers due to cost, and RTB House's findings pointed to a K-shaped economy where spending pressure is unevenly distributed. One of the more surprising patterns: younger cohorts were more likely than older ones to say they planned to spend more, challenging the assumption that spending resilience is concentrated among older consumers. For marketers, that means the growth path is getting longer and less linear. Winning no longer comes down to the last click. It requires staying visible and relevant throughout an extended consideration cycle and across every device and touchpoint involved. Trust, fulfillment and measurement will define the winners. If discovery is fragmenting and behavior is becoming more complex, the webinar made clear that trust, fulfillment and measurement will be critical differentiators in 2026. Forrester emphasized that Amazon's advantage isn't just scale, but trust in the post-purchase experience - reliable delivery, easy returns and consistent service. That standard now shapes expectations across ecommerce, with B&H Photo reinforcing that the real work often happens during and after the transaction to drive repeat customers. On measurement, RTB House highlighted the need to move beyond platform-reported performance toward true incrementality. Attributed results can be misleading, making unbiased testing and clear success metrics essential for understanding real impact. As media fragments across channels, marketers should align measurement to each tactic's role - using transactional metrics for lower funnel and awareness or consideration metrics for upper funnel. Finally, Forrester noted that while shopper-facing AI commerce is still early, "agentic under the hood" use cases are already delivering value - pointing brands toward practical, ROI-driven AI applications over hype. CommerceNext steps. * Peak ambiguity demands proactive leadership. Plan ahead, advocate strategically and collaborate to stay ahead. * Discovery is fragmenting. Balance innovation with proven channels. Test new platforms, but protect high-performing search and social. * Trust and fulfillment remain core differentiators. Consumers still default to Amazon - AI-first leaders can capture the gap. * Consumer behavior is now age-driven, research-heavy & multi-device. Marketers must meet shoppers on every channel and win the long consideration phase - not just the last click. Want more insights on what's next for retail growth, AI and ecommerce strategy? Join CommerceNext, LLC June 23-24 in NYC for the 2026 CommerceNext Growth Show by registering today.

Email Vendor Selection
Mar 26th, 2026
First take on the Forrester Wave Email Marketing Service Providers 2026.

First take on the Forrester Wave Email Marketing Service Providers 2026. Forrester's latest Wave on Email Marketing Service Providers arrives at an interesting moment for the category. For years, these evaluations felt largely static... the same capabilities, the same positioning, the same incremental shifts. This one is different. Not perfect, but more aligned with the direction the market is heading. This time around, there's a lot here they get right. And I know it must be surprising to many of you that that's the first thing I write! But before you think I've gone soft, there are still a few things they don't exactly get wrong, but they struggle to explain. What Forrester gets right: email is no longer just email. The Wave report states that "Email marketers using this evaluation to inform a purchase decision should look for: AI as a functionality-enabler, not as a feature." That may sound subtle, but it's a significant evolution in Forrester's thinking. It's the single most important shift in this Wave. Since the beginning of time, Forrester's ESP evaluations have focused on message composition, deployment infrastructure, and reporting. In other words, email as a production system. This latest Wave acknowledges something more important: email is now part of a broader system of decisioning, orchestration, and interaction. The emphasis on conversational interfaces, AI-driven timing and targeting, and dynamic content assembly signals a move toward what modern ESPs are trying to do: turn signals into action, in real time. That's a huge step forward in Forrester's thinking. Another positive outcome in the current Wave is that Forrester appears to be notably more disciplined in how it evaluates AI. Rather than rewarding vendors for the number of models or agents, they focus on how AI reduces marketer effort, improves workflows, and ensures transparency. Forrester highlights vendors that "applied AI to amplify sophistication, relieve marketer stress, or introduce opportunities." That's exactly the right lens. Because in practice, the value of AI in email marketing isn't what it produces, it's whether anything actually happens because of it. The leader board: directionally right, but not fully explained. The placement of vendors in this Wave broadly reflects where the market has been moving. But the report provides limited visibility into what drove the more dramatic shifts. Take Adobe. Adobe's rise to a leadership position is perhaps the most notable movement by a vendor compared to the previous Wave in 2024. The report cites content strengths, responsible AI, and orchestration capabilities. All valid. But what's missing is a clear articulation of what fundamentally changed in Adobe's architecture or execution model over the past two years to justify that leap. For many enterprise teams, Adobe Journey Optimizer still requires coordination across multiple systems, which introduces complexity, latency, and operational cost. The Wave acknowledges Adobe's strengths but doesn't reconcile them with those tradeoffs. Vendor inclusion still feels inconsistent and arbitrary. Forrester outlines their inclusion criteria as: "Broad, enterprise-level support... substantial revenue... and mindshare among Forrester's enterprise clients." Yet the actual vendor set raises questions. In the 2026 Wave vs. 2024, Klaviyo is now in, and Optimove is out. Klaviyo's inclusion makes sense given its growth. But the absence of Optimove (without a clear explanation) highlights a recurring issue: vendor coverage feels inconsistent. Notably absent from this evaluation are platforms like MessageGears and MoEngage. Both meet enterprise criteria and represent meaningful architectural approaches. Leaving them out limits the usefulness of the evaluation. Forrester's claim that the report features "The 12 Providers That Matter Most" doesn't hold up to scrutiny. What's still missing: architecture. Forrester evaluates features, strategy, and customer feedback. And yes, it does assess important architectural components like data management, identity, and governance. What's still missing is a clear view of how those elements come together to impact execution. That's where the real differences show up. * How quickly can a platform recognize a signal? * How quickly can it act on it? * How many systems are involved in that loop? Those questions ultimately determine speed, scalability, and cost. But they're difficult to see in a feature-based comparison. Forrester correctly highlights that AI is changing what email marketing platforms can do. But AI makes architecture more important, not less. Because AI depends on clean, connected signals and the ability to act on them quickly. If those break down, the AI doesn't matter. Closing thoughts. The market is no longer divided by features or UI. It's divided by how tightly data, decisioning, and execution are connected. Some platforms embed these capabilities. Others orchestrate across systems. Both can work, but they create very different operating models. This is one of the stronger ESP Waves Forrester has produced in recent years. It moves beyond feature checklists, treats AI more realistically, and reflects vendor momentum. But it still stops short of addressing architectural differences, vendor inclusion consistency, and operational realities. The result is directionally right, but not yet complete. So what should you take away from the 2026 Wave? Don't just look to see who are marked as Leaders and leave it at that. Ask yourself how the platforms would operate in your environment, how each moves from signal to execution, and what each costs to run. Because increasingly, the difference between platforms isn't what they can do, it's how efficiently they can do it in the real world. Contact Email Vendor Selection (or Email Connect) if you'd like expert help selecting the best email marketing platform for your business. About Chris Marriott. Chris Marriott is a trusted advisor to enterprise brands selecting and operating modern ESPs/engagement platforms. He's the President & Founder of Email Connect, a consultancy that for the last 10 years has helped leading brands, including American Airlines and TJX Companies, navigate complex vendor ecosystems and avoid costly technology decisions. A 30-year veteran of digital marketing, including well over 20 years in email marketing, Chris is a recognized expert in the martech vendor landscape and vendor evaluation process. Prior to founding Email Connect, Chris served as a tenured executive at Acxiom, building and leading its Global Digital and Email Agency Services team into one of the industry's top agency services providers. Additionally, he is a regular speaker and columnist on the changing martech landscape and the RFP process and is an adviser to several emerging marketing technology companies. He holds a BA from Dartmouth College.