Forrester

“Strategy without tactics is the slowest path to victory. Tactics without strategy is the noise before defeat.” — Sun Tzu, “The Art of War” Customer success (CS) practitioners often talk to me about postsale strategy and tactics. What I’ve noticed from those conversations is that those terms are being used interchangeably despite being different, though complementary, concepts. In Forrester’s State Of Customer Engagement Survey, 2024, however, we found that CS teams over-rotate on the tactical. Our data overview report on B2B customer success responsibilities shows that only about a quarter of CS practitioner activities are strategic. Only three strategic CS responsibilities — customer segmentation, establishing strong relationships with decision-makers and key stakeholders, and determining overall strategy for the customer’s postsale experience — rose to the top 12 customer success remits. The other nine responsibilities in the top 12 are tactical. Tracking goals and sharing progress toward customer outcomes — joint customer success plans — barely registered. If the long-term goal of CS is to positively influence retention, customer outcomes should be near the top of the list. If any of this resonates, reassess your CS strategy. To succeed, CS must have the right charter, investment, alignment with the business, and ability to manage the customer journey. If you haven’t revisited your strategy in a while, now is the time to do so. Your CS strategy must evolve to ensure that it’s in lockstep with the company’s goals and the changing needs of your market. To read more about where customer success teams spend their time and other challenges they’re facing, dig into our data overview report, 2024 Data Shows Customer Success As Less Reactive But Still Tactical. And if you’d like to assess your own customer success strategy, reach out to your account team to schedule a guidance session with us. source

Three Steps To Prepare For Your PLM Evolution This time last year, we found that more than half of manufacturers planned to replace or upgrade their product lifecycle management (PLM) platforms. Why? Because massive changes in markets, regulations, and technology drive the need to develop distinctive competencies in product innovation. To help with this transition, we have recently published research on three needed steps to transform PLM. Below is a summary of a three-step process that tech leaders should follow by reviewing their PLM practices, platforms, and partners. Step 1: Overhaul PLM Practices You should review your existing PLM practices first and: Decompose engineering artifacts from documents to data. To boost concurrent design, modern PLM decomposes documents and models into atomic elements. You should selectively encapsulate data for collaboration. Explore modeling languages to simplify complex system design. Consider the example of Ford using modeling language SysML to specify, analyze, design, and document complex systems. Step 2: Review PLM Platform Options Once you have reviewed your PLM practices, you should review your PLM platform options, namely thinking about their support for concurrent design and engineering change management. Concurrent design accelerates time to market but depends on platform support for scalable multi-enterprise and -disciplinary collaboration. You should: Understand vendors’ offerings. Vendors’ adoption of systems engineering standards will help you migrate to the cloud as well as integrate PLM and other enterprise applications such as product information management. Boost product introduction success rates with AI-ready composability. Review the incidence of late-stage engineering changes because of unexpected test results. Consider dynamic test and retest process reconfiguration capabilities to help maintain a competitive new product introduction cadence. Scale product innovation from personal to planetary. Review platform providers’ cloud deployment roadmaps. You should use them to underpin your own global collaboration and inform your plans for role-based user-experience personalization, extensibility, and integration. Refocus PLM processes from engineering to enterprise. Select a data architecture that enables product and business model innovation. You need vendors’ support for open API specifications — from groups such as OSLC — that capture the meaning of data shared with other apps, like sales teams’ quote-to-order solutions. Explore platforms’ compatibility with API frameworks and data catalogs. Consider managing data and metadata across engineering disciplines using general-purpose data cataloging and API frameworks for both data cataloging and event monitoring. Now that manufactured products and assets include mechanical, electrical, electronic, and embedded software elements, platforms must also support multidisciplinary engineering change management (ECM). You should: Rethink engineering change management. Rethink your ECM process using your chosen vendor’s platform to synchronize engineering changes across multiple suppliers in different supply chain tiers and across engineering disciplines. Focus on platforms’ potential to support changes in manufacturing volumes and variety. Perpetual ECM means that you need a product data model embracing desktop and departmental data accumulated over years of legacy PLM work-arounds and customization. Check platforms’ ability to link asset lifecycle events to data authoring and consumption. Think about the way that critical PLM events — from staging and construction to commissioning and operating — trigger different parties to author, approve, or consume product or asset data. Assign data stewardship responsibilities early in your PLM evolution planning. Step 3: Enlist PLM Partners When you are finished with modernizing your PLM practices and reviewing your PLM platform options, you should recruit systems integrators (SIs) to help: Pave the path to PLM paradise. Review SIs’ tool and expertise offerings that mitigate the dull daily challenges of locating and maintaining data. Identify authoring applications. SIs can help identify all the “author” applications that engineering and testing roles use to generate structured or unstructured data and content for aggregation and consumption by manufacturing, marketing, and service roles. Apply the lessons of cloud mobile architecture. Work with SIs to develop role-specific applications that consume PLM data. Reflect regulatory and legal requirements. SIs label legacy data by taking account of context such as the client’s regulatory framework to establish selective viewing and editing authorizations. Please schedule an inquiry with me if you would like to discuss your own path to PLM paradise. Also, look out for our March 2025 refresh of the PLM landscape report. source

The proactive security market is consolidating further as exposure management vendor Tenable announced its intent to acquire Vulcan Cyber, a unified vulnerability management (UVM) vendor that specializes in third-party vulnerability collection, vulnerability response, and application security posture management. This acquisition demonstrates how vendors are reacting to CISOs’ continued need to unify and consolidate their fragmented arsenal of security tools. Tenable plans to complete the acquisition by the end of March 2025 for $147 million in cash and $3 million in restricted stock units. Forrester estimates Vulcan Cyber’s annual recurring revenue at around $25 million with about 100 enterprise customers. This acquisition underscores Tenable’s commitment to enhancing vulnerability response, complementing its recent announcement of adding support for integrated patch management capabilities. As attack surfaces expand across cloud, devices, and applications, security teams face the challenge of managing diverse security posture assessment tools that identify various assets and assess vulnerabilities. This fragmentation makes vulnerability prioritization and remediation tracking challenging. UVM companies such as Vulcan Cyber consolidate and unify vulnerability sources from cloud security, vulnerability scanners, endpoint security, and more to aid in the prioritization process. This unification allows teams to apply prioritization methods and orchestrate and track remediations effectively. This acquisition further aligns with Forrester’s research on proactive security, which is made up of three core principles: visibility, prioritization, and remediation. Vulcan Cyber’s model of unified vulnerability management, which ingests third-party vulnerabilities and improves response, addresses areas where Tenable has traditionally not been as strong. Forrester expects Tenable to prioritize integrating Vulcan’s third-party connector ecosystem into its Tenable One platform and leveraging Vulcan’s application security posture management (ASPM) capabilities. This integration will enable Tenable One customers to pull in more diverse vulnerability sources, from static application security testing/dynamic application security testing to cloud security providers, ultimately improving remediation response workflows and insights. UVM solutions have recognized the advantage for security leaders of being able to ingest, aggregate, deduplicate, and triage findings from various vendors and types of application security testing tools. ASPM solutions such as Vulcan Cyber advance this approach by correlating issues discovered during development and testing with application deployment and runtime information. The contextualized prioritization focuses development and DevOps teams on addressing only the most important business-impacting issues, thereby enhancing development productivity and minimizing risk. Moreover, Vulcan Cyber’s ASPM offering further allows Tenable to capture a larger share of the application security budget. With this acquisition, Tenable has expanded its vulnerability management to enhance remediation. Vulcan’s workflow engine allows security and IT teams to build and deploy custom playbooks that automate prioritization and remediation process, reducing manual overhead. Tenable One can leverage Vulcan’s ability to seamlessly bridge vulnerability data with DevOps toolchains. This acquisition marks Tenable’s fifth in three years, following purchases in data security (Eureka Security), cloud security (Ermetic), attack surface management (Bit Discovery), and exposure management (Cymptom). The proactive security market is expected to continue consolidating through acquisitions and the unification of vulnerabilities and assets from disparate tools. source

What makes DeepSeek’s R1 such a breakthrough in cost efficiency? Learn the details and benefits of nine innovations behind the R1 technology. source

Forrester’s annual State Of B2B Events Survey is back! We invite all B2B event leaders and practitioners to participate and gain access to the latest B2B event market trends to help shape their event strategy over the next 12 months. Last Year’s Survey The 2024 iteration of the survey delivered a number of insights into the evolving event mix, priority focus areas, and approaches to event technology: Two-thirds of marketers faced flat or declining event budgets. While the event mix is now multiformat, small and hosted events were by far the fastest-growing event format type in 2024, followed by webinars. Better event measurement, maximizing the value of event data, and improving post-event attendee follow-up were the top three priorities. There were stark regional differences when it came to sustainability, with 79% of EMEA teams saying that this was a priority compared to just a third of North American teams. Only one in five organizations had integrated their primary event technology platform with their wider infrastructure, leading to data silos. 2025 Survey Overview While events continue to dominate marketing program spend in 2025, teams face an uncertain and challenging environment. Budgets remain under pressure, younger attendees want different experiences, and technology remains siloed. To thrive, teams must align event plans to business objectives and attendee needs and do a better job measuring event impact. The 2025 State Of B2B Events Survey will delve into key topics to help leaders understand the environment, including budgets, event mix planning, priority focus areas, and attitudes about AI. Confidentiality And Benefits Rest assured that all survey responses will be kept strictly confidential. The survey itself will take less than 15 minutes to complete, and all respondents will receive a complimentary copy of the Forrester reports, The Global State Of B2B Events, 2024: Marketers Continue To Ride A Wave Of Transformation and Reimagine B2B Events With AI. We will also share a summary of the findings when available in Q2. Join The Survey Your input is invaluable to us! If you’re involved in running B2B events, take the 2025 State Of B2B Events Survey before February 21. For any questions, please don’t hesitate to reach out to Conrad Mills ([email protected]) or Hannah Jachim ([email protected]). source

The Forrester Wave™: Content Platforms, Q1 2025, is now live! We looked at 12 key vendors and evaluated them on 24 criteria. Four Leaders emerged, followed by five Strong Performers and three Contenders. To learn more about these vendors and how they serve their target markets, Forrester clients can view the full report. Get Ready For A More Intelligent Approach To Content Management The enterprise content management market has undergone a significant transformation and today is exemplified by AI-enabled cloud content platforms. Generic document management doesn’t cut it. Technical leaders and the business roles they support want flexible, extensible platforms on which to design and deploy a range of content-rich apps. Content platforms are a foundational component of an overall digital workplace, integrating with key productivity suites and essential enterprise applications. A Fast Pace Of Innovation Marked This Year’s Evaluation Our Wave methodology ensures that we do a deep dive into the evaluated content platforms, looking at extensive written questionnaire responses from vendors, sitting through demos and briefings, and talking directly to their customers. I found that: The pace of innovation over the last two years has been unprecedented — driven by AI. Generative AI (genAI), is transforming how we create, consume, and govern content. Vendors are making substantial investments in genAI, with capabilities evolving quickly as large language models and agentic AI continue to develop. This rapid iteration means that businesses can expect continuous improvement, including evolving pricing models to put more AI capabilities into users’ hands. Automation opportunities abound. From simple document approvals to complex processes that integrate with other enterprise applications, the range of automation capabilities is expanding. Intelligent data extraction helps fuel high-volume, document-centric workflows and automates metadata identification and tagging. Document generation capabilities, increasingly assisted by AI and integrations, continues to be an area of investment for vendors. Packaged apps and solution templates can fast-track adoption and productivity. Many vendors have mature vertical strategies and have packaged apps designed specifically for industry-specific use cases. Look for predefined templates or solution accelerators to tailor your deployment to meet specific business needs — often with minimal custom development. Key Considerations For Buyers Not all vendors are ideal for every content management use case. When building a shortlist for content platforms, keep in mind that: Vertical expertise matters, and not everybody has it. Look at the vendors that understand the nuances of your industry and that invest in the solutions, professional services, and partner ecosystem to meet your requirements. Vendors focusing on key verticals will invest in meeting industry-specific compliance obligations, obtain certifications, and help clients meet their regulatory requirements. Pricing models are simplifying — but becoming opaque. While a handful of vendors in this evaluation do publish the pricing for their most common subscription bundles, most don’t. Most vendors price their cloud content platforms on per-user/per-month models with a choice of a few subscription tiers, such as basic, intermediate, or advanced capabilities. Vendors that still offer self-hosted or on-premises deployment options may have additional pricing and licensing models tied to API calls, storage volumes, or other usage- or application-based parameters. Know your use cases and your requirements when you reach out to vendors that don’t publish pricing/licensing models. Context matters when trying to get value out of genAI. Bring AI to your content rather than bringing your content to AI. Using the embedded genAI capabilities from your content platform vendor can provide an unfair advantage. Most evaluated vendors are using a retrieval-augmented generation architecture that shields your corporate content from public AI models, and also respects existing access controls and permission structures. Exposing a genAI assistant in a folder, a workspace, or search result interface can ground the AI in the that specific context — i.e., a customer case, a project folder, or list of incoming claims — to return specific answers and relevant citation links to source documents. Interested in learning more? I’ll be hosting a webinar for clients on Thursday, March 6, to go over the key findings from this Wave. Join us by registering here! Forrester clients are encouraged to set up a guidance session or inquiry to talk about our key findings and learn more about this market. source

Last week, Forrester hosted our Predictions 2025 Webinar: Technology & Security. We had a great time bantering about some of the most impactful security and technology predictions that our analyst teams called out, including around the ROI for AI initiatives, private cloud and VMware, plans for agentic AI, and enforcing the EU AI Act in 2025. Thanks to the webinar attendees who asked some insightful questions throughout the session! Unfortunately, we ran out of time and couldn’t answer all of your questions, but here are responses to some of the questions we couldn’t get to (questions have been edited for clarity): Which application types will be best suited for on-prem clouds? Private cloud can’t remotely match the firepower, scale, and pace of innovation of the hyperscale public cloud platforms, but this doesn’t mean that private cloud is irrelevant. In fact, private cloud may be the most cost-effective choice for much of enterprise IT, particularly in shops that embrace the enabling style of high-performance IT that focuses on stabilizing and protecting operations that are cost-effective and don’t require vast cloud resources. Then there are workloads where security and sovereignty are paramount and where the autonomy of enterprise IT is critical. Even IT organizations embracing the transforming style of high-performance IT may find that private-cloud-based AI meets their needs, especially if DeepSeek’s claims of AI innovation on garden-variety GPUs become generalized. Do you suggest a formula or criteria to help stakeholders select high-value business use cases for AI? There is no formula, per se. A good way of thinking about it is in the form of a portfolio of use cases and capabilities that are road-mapped with interconnected milestones — some of which deliver quick value and others more so over the longer term (because for some use cases, even high-value ones, it may be better to wait or go slow). Use case selection is complicated for AI and not just driven by monetary value but involves readiness based on four teams: business, data, technology, and governance. Have you observed any recurrent behavior in how and who is writing the AI agenda? Any emerging pattern (e.g., centralization, federation) as the practice evolves in each organization? In Forrester’s State Of Data, Analytics, Measurement, And Insights Survey, 2024, we asked data and analytics decision-makers, “Where does the most senior data and analytics leader report to in your organization?” Thirty-nine percent of respondents say IT and 37% say to the CEO — so the agenda is set by IT leaders or the CEO, as discussed in the webinar. We are seeing a lot of partnership between business and IT and federation. Thinking more about security than AI, I see AI as creating an even higher priority to cover the basics to reduce exposure and risk. Do you agree? We covered this briefly at the end of the webinar, but it deserves a longer response. As we build AI into our systems and applications, a lot of the risks and challenges should look familiar: unprotected API calls into third-party models, unvetted models, and shadow AI. Over the years, we’ve learned lessons about third-party risk management, using open-source and third-party software components safely, and managing and protecting APIs — we need to apply those lessons to AI so that history doesn’t repeat itself yet again. How well are third-party risk management systems factoring risks around AI governance? Many of the platforms that support third-party risk management (TPRM) also enable governance, risk, and compliance (GRC) use cases. These platforms support AI governance by helping organizations get a handle on the range of AI use cases that their companies deploy and the variety of models that support them — inventory assets, systems, and third-party entities, as well as support AI policy creation, distribution, and tracking. Generative AI features of GRC and TPRM platforms have quickly become standard to how risk pros manage the risks of AI in their organizations. Additionally, AI governance platforms are emerging as a new market forecasted to grow at a 30% compound annual growth rate to the end of this decade. There’s more to come on this, with Forrester planning new, groundbreaking evaluative research on AI governance platforms in 2025. Thanks again to all the attendees who asked such insightful questions! If you missed the webinar, you can still check out the replay here. Forrester clients, be sure to check out all of our 2025 Predictions reports and set up an inquiry or guidance session if you want to dive in further. source

The Challenge With The Circular Economy In 2025, Forrester predicted that more than a third of Global Fortune 100 firms will commit to circular economy goals. We recommended that, this year, enterprise leaders perform infrastructure lifecycle assessments to understand the environmental impact of their choices. Further for manufacturing, Forrester’s report, Embrace The Circular Economy To Make Manufacturing More Sustainable, describes five Rs that matter for manufacturers: reduce, reuse, repair, refurbish, and recycle. For IT, however, circular economy practices face challenges. Some of these key obstacles include: Enterprise. Shifting habits toward more sustainable practices can be difficult. IP and proprietary ecosystems. Existing regulations around IP may not always support circular practices and can sometimes incentivize waste. Economic incentives. The initial investment for transitioning to circular models can be high, and the economic benefits may take time to materialize. Infrastructure availability gaps. Adequate technology infrastructure for recycling and reusing materials isn’t always available. The challenges are magnified by rapid technological shifts, power demands, limited resources, and the increasing importance to nations, their businesses, and their citizens globally. Firms need to identify whether they need to dispose (as with the linear economy) or recycle the asset and its components. Tech leaders must know the asset value within and outside the organization. This data is the key to making an informed decision and whether keeping or recycling an IT asset (and its components) is more valuable or sensible. But this critical information is currently lacking and can drastically change the decisions made today. The CARFAX Approach At Forrester, we propose gathering information about IT assets and their service records, much like CARFAX does for used vehicles. This doesn’t address all the challenges of circular economy, but we believe that it’ll assist in mitigating the impact of many of them. One of the recent developments in this area has been the French repairability index. The CARFAX approach will address some of the challenges so far debated in this approach, such as: Not relying on manufacturer self-assessments. Wider scope — IT in the data center as well as IT in the workplace (end user devices). Focus on both availability and affordability. How To Get This Information The information needed to enable this approach is already available for many IT organizations, via a configuration management database or bill of materials that contains the information of IT assets and service tickets for those IT assets. Understanding whether an IT asset is up to date with the latest firmware and patches, has had parts replaced, has had issues, or has been kept in an environment that’s out of specification helps an organization understand the value of what they have: Is the IT asset worth keeping? Is it better to recycle or dispose of it? Can you sell/auction it to recoup some capital? Who Can Build This Dataset? An independent third party can help your organization by letting you know the market demand for those IT assets, the available supply, and its value. This information enables tech leaders to make the right decisions with their IT assets. Without the critical context of this data, organizations may not make optimal decisions on whether to retain, reuse, or dispose of IT assets. After all, these decisions cost money, time, effort, and may face risks by using failure-prone IT infrastructure. This Is Just The Start Parts of this approach involve having an independent entity on board. What that entity would look like — wholly private, nonprofit, or a public entity — is open to debate. There are parts of the CARFAX approach that still need to be addressed: The need to handle sanctions and export controls between countries Transparency and trust with the entity Requiring the entire ecosystem (organizations, server vendors, support providers, etc.) to be involved in data sharing to enable this approach Dependence on the reported data (must be accurate, comprehensive, and up to date) source

Generative AI (genAI) for visual content is the subject of many memes — think pictures of humans with three hands. But while the technology is not yet perfect, it’s gaining traction across industries, from retail and manufacturing to insurance and the public sector. Organizations are leveraging this technology to create immersive and interactive customer experiences such as virtual try-ons and hyper-personalized marketing campaigns, as well as virtual simulation environments and AI designs. While many have heard the buzz around AI-generated images, the real transformation is much broader. GenAI isn’t just generating captivating visuals; it’s reshaping how businesses scale creativity, engage audiences, and develop entirely new products. GenAI Revolutionizes Content Productivity Until recently, creating compelling visual content required large budgets, specialized design and production teams, and long production lead times. Now, advanced AI technologies such as generative adversarial networks, diffusion models, and transformer-based architecture can generate, enhance, or remix images and videos in ways that were unimaginable just a few years ago. This means more agility and a faster path to market for creative assets. Forward-thinking firms are already using genAI to prototype products, localize campaigns for different regions, and customize content at a pace that was not possible with traditional methods. Opportunity Knocks, But So Do The Pitfalls Several converging factors are propelling genAI for visual content into the spotlight: Cost and speed. AI-based tools dramatically reduce design and production timelines, providing near-instant variations of an image or video for different target audiences. This creates the opportunity to produce quality content in a fraction of the time previously required and at a fraction of the cost. Engagement and personalization. Fast and cheap are not the only advantages. GenAI for visual content also helps enterprises meet consumers’ demand for relevance. GenAI enables brands to tailor visuals to individual preferences — whether it’s a try-on avatar mirroring the user’s body type or localizing imagery for numerous global markets. Interactive experiences. Beyond static images and video, companies are exploring AI-powered 3D renderings, augmented-reality demos, and dynamic ads that respond in real time to user behavior. Of course, it’s not all smooth sailing. Even as businesses rush to harness genAI’s visual content potential, concerns about copyright, data privacy, and brand integrity arise. Organizations also face mounting regulatory pressures, especially in regions like the EU, where the EU AI Act imposes stringent guidelines for AI-generated media. At the same time, ethical considerations loom large, from ensuring fair training data to avoiding deepfake misuse, and photorealism or visual quality is still a concern for brands that command a premium in the marketplace and require high-quality visuals to match. From Synthetic Moments To Governance: Create A Balanced GenAI Game Plan Executives need a holistic approach that weaves together technology, business, and culture to maximize the impact of genAI. This means tailoring AI-generated experiences for the right consumer moments — using synthetic visuals for scrolling or gaming while preserving authenticity for live encounters such as in-store shopping. It involves freeing employees from repetitive tasks through automation and reserving creative, strategic work for human insight. Finally, leaders must establish solid governance, aligning with emerging global regulations to ensure responsible innovation and effective risk management. Our newly published report, The State Of Generative AI For Visual Content, 2025, illustrates how genAI for visual content brings the promise of scaled production, content personalization, and immersive consumer experiences to life. Forrester clients can read this report to learn about the trends, use cases, and short- to midterm benefits. Clients can also read Maximize The Magic Of AI Visual Content to better understand the risks/rewards of using visual content tools or The State Of Computer Vision Technology, 2024 to understand how advancements in machine learning, enhanced computing power on devices like smartphones, and increased data availability have accelerated the adoption of computer-vision-powered applications. And of course, clients can also connect with us through an inquiry or guidance session to discuss genAI for visual content solutions or other associated topics. source

AI advancements have caused deepfakes to emerge as a significant threat that B2B CMOs and brand leaders cannot afford to ignore. These synthetic audio-visual impersonations can mimic real individuals with alarming accuracy. As this technology becomes more accessible, the potential for misuse grows, posing risks to businesses’ reputations, stock prices, and overall trust. The Immediate And Long-Term Impact Of Deepfakes Deepfakes are not just a distant threat; they are a present danger with the potential for long-lasting repercussions, as they can target corporate executives, disrupt business operations, and erode stakeholder confidence. To mitigate deepfake risks, marketing leaders must understand the following factors: Common nefarious motivations. Deepfake creation is often driven by malicious motivations. Disgruntled employees may use deepfakes to seek revenge, leveraging their insider knowledge to make the fakes particularly convincing. Competitors and business partners might deploy deepfakes to gain leverage in negotiations or undermine the other party, leading to mistrust and strained relationships. Cybercriminals may create deepfakes for financial gain, threatening to release damaging fake videos or impersonating executives to authorize fraudulent transactions. Blurred lines between truth and believability. The illusory truth effect and the reiteration effect are psychological phenomena that play a crucial role in how deepfakes can deceive audiences. These effects refer to people believing false information to be true after repeated exposure, regardless of their actual veracity. A well-crafted fake, if seen multiple times, can start to be accepted as genuine. Social media platforms amplify this problem by rapidly spreading misinformation, making it increasingly difficult to distinguish fact from fiction. A strong brand reputation can help combat the believability of deepfakes, but companies with lesser-known executives are more vulnerable to these risks because the fact-from-fiction challenge is amplified given their relative obscurity. Positive deepfakes and ethical dilemmas. Deepfakes can also be used positively in business contexts. AI agents and executive clones can serve as hyper-realistic customer service representatives or deliver speeches and attend meetings on behalf of the real executives themselves. Without adequate transparency and disclosure, these positive deepfakes can mislead customers and stakeholders, undermining trust.   The Urgent Need For Preparedness Despite the clear risks, many B2B marketing leaders are not adequately prepared for deepfake threats. Forrester’s 2024 B2B Brand And Communications Survey reveals that a significant percentage of marketing leaders are concerned about deepfakes, yet few have implemented robust strategies to monitor for and counter them. To protect their organizations, CMOs must: Prioritize the threat. Recognize deepfakes as a critical risk, and allocate resources to mitigate them. Evaluate the risks, and partner with functional leaders, the CISO, and legal teams to combat any threats. Build a robust crisis response plan. Develop and practice crisis communication strategies that include deepfake scenarios. Regularly conduct simulations to ensure readiness and identify gaps in the response strategy. Establish and maintain a strong brand. Not only do brands have to navigate deepfake threats, but they must build trust in an era of increasing “deep doubt,” where there is skepticism toward all media. A strong, trusted brand will have greater believability and recover more quickly from a negative deepfake event. By prioritizing deepfake preparedness, building robust response plans, and fostering strong internal partnerships, CMOs can safeguard their brands against this emerging threat. The time to act is now, before a deepfake incident causes irreparable damage. Forrester clients can access the report, Deepfakes: The Hidden Threat CMOs Can’t Ignore, and schedule a call with us. source