Forrester

The AI Transformation In Accounts Receivable In the dynamic world of finance, AI is transforming accounts receivable (AR) processes, driving efficiency and accuracy like never before. Our latest report, Top AI Use Cases For Accounts Receivable Automation In 2025, explores the groundbreaking ways AI is reshaping AR, from collection management to electronic invoice presentment. The report highlights five key use cases where AI is making a significant impact: Collection management. AI technologies such as ML and predictive analytics are enhancing collection management by assessing at-risk payments and forecasting overdue account recovery. Companies like Serrala and BlackLine are leveraging AI to tailor collection strategies and forecast invoice payments, improving collection prioritization and efficiency. Cash application. AI is streamlining cash application processes by analyzing historical invoice and payment patterns to automatically apply new incoming payments to open invoices. Solutions from Quadient and HighRadius are automating payment allocation and providing personalized insights on payments and invoices. Payment notice management. AI-driven text analytics, ML, and generative AI (genAI) are optimizing payment notice management. Quadient uses ML to categorize inbound AR emails, while genAI generates email replies and templates to save employees’ time. Deduction management. AI is significantly automating deduction management, particularly in the consumer packaged goods and retail industries. HighRadius uses prescriptive analytics to prioritize deductions based on their likelihood of being invalid, while Serrala’s predictive AI analyzes past behavior to predict unauthorized deductions. Electronic invoice delivery and presentment. AI is enhancing e-invoice delivery and presentment by automating the generation of invoices in compliant formats. Serrala uses genAI to convert complex e-invoices to PDFs for quick review by auditors and approvers. Choose The Right AR Use Case Our report also features two insightful heatmaps that illustrate AI’s impact on AR automation. These heatmaps provide a clear visual representation of AI adoption among enterprises (see below graphic) and future investment priorities across various AR use cases, helping finance and technology leaders make informed decisions about their AI strategies.   The future of finance is bright with AI at the forefront. By adopting the right AI technologies, companies can achieve significant improvements in efficiency, accuracy, and cost savings in their AR processes. Dive into our full report, Top AI Use Cases For Accounts Receivable Automation In 2025, to explore these insights in detail and prepare your organization for the AI-driven future of finance. Forrester clients can schedule a guidance session or inquiry with me to discuss this topic more. source

Technology service spending will reach $2 trillion in 2028, rising 4.6% year over year globally, much faster than GDP growth. We recently analyzed the earnings of six technology service providers and surveyed over 2,300 enterprise service decision-makers (with both business and IT titles) from 11 countries around the world to find out what’s going on out there. We have done a three-part analysis of the state of technology services: 1) co-innovation services; 2) provider selection, pricing, and management; and 3) strategic partnerships. Here are some highlights: Strategic service providers must be co-innovation partners, not just job shops. The primary driver of change in services is co-innovation. In this model, providers share risk and are motivated to achieve specific outcomes. They help you coordinate internal stakeholders and orchestrate cloud, software, and AI ecosystem providers. At the heart of co-innovation partner relationships is trust, which, at 47%, is the most important factor in selecting a provider. Providers’ growth stems from demand for core transformations … The days of random projects that didn’t move the needle on business growth or profitability are over. After 15 years of projects, firms are consolidating into core systems and laying the software, data, and process groundwork for the next wave of growth. In a recent earnings call, Cognizant emphasized “large deals” (code word for transformation or outsourcing) driving “fourth-quarter bookings [increasing] 11% year over year.” … and for a new wave of AI business investment. Almost half of respondents we surveyed say that AI is the most important technology for third-party services help — internet of things came in a distant second at 9%. During a December 2024 earnings call, Accenture CEO Julie Sweet reported $1.2 billion in new AI bookings and went on to say, “Those who really want to go into AI are more prioritizing spending as opposed to spending more.” Firms want results — not just people — and they’re willing to pay to achieve it. The survey reveals how prominent performance-based pricing models have become as a way to achieve outcomes, motivate providers, and share risk. In 2024, 45% of services decision-makers expected to expand their use of performance-based pricing and 46% expected to increase fixed-price contracts. We expect providers to make more fixed-price bids as they build generative AI-powered delivery platforms that improve delivery speed, quality, and predictability. Providers respond by amping up asset-driven business models. Thirty-five percent of North American and 38% of Asia Pacific respondents see data, content, and software assets as key benefits to working with service providers. Interestingly, only 25% of European services decision-makers are focused on a provider’s assets. With genAI disrupting service delivery economics — more value at lower cost — it’s important that providers bring more assets and solutions to help enterprises gain an AI advantage. Manage Service Providers To Maximize The Value They Bring The survey provides solid benchmarks for effectively managing providers, including these best practices: Regularly meet with your providers. Fifty-two percent of service decision-makers hold quarterly or even monthly meetings with providers to plan the roadmap for the next phase of their projects. By maintaining open lines of communication between providers and employees, organizations establish an integration strategy that fosters collaboration and ensures a cohesive approach toward objectives. Track quality and financial metrics to assess provider engagement levels. Survey respondents report that their organizations monitor key metrics such as quality (54%), financial performance (48%), and end user experience (47%). Organizations should develop a repeatable scoring method based on these metrics as a best practice to align their organizational goals with their partner’s plan. Ensure that providers satisfy stakeholders. Forty-one percent of decision-makers assess providers’ engagement using senior stakeholder satisfaction. Involving stakeholders in the evaluation process provides diverse senior-level management perspectives and helps gather insight into their performance and partnership qualities. If you want to dig deeper into co-innovation to maximize the value of partners, please reach out to me by scheduling a guidance session or an inquiry via email: [email protected]. If you have an offering that moves the needle on co-innovation, performance-based pricing, AI-powered delivery, or ecosystem orchestration, please consider scheduling a briefing: [email protected]. source

Although not a new technology by any stretch, web application firewall (WAF) solutions continue their evolution. Today, WAF solutions are cloud-based and protect applications and APIs in hybrid and multicloud environments. WAF solution vendors have expanded their remit to address API attacks and layer 7 DDoS and are working to integrate WAFs with bot management, API security, and client-side security tools to offer complete application protection platforms. This is good news for security pros, who continue to face an onslaught of application-based attacks. To execute successfully, security teams must operate more efficiently than ever and rely on a WAF solution that will limit/eliminate false positives, avoid performance lags, prevent outages, and more completely block attacks that would threaten their credibility with the product team and the business as a whole. Customers purchasing new WAFs or looking to upgrade their current WAF must consider: The best range of features to protect business-critical apps. WAF solution deployments struggle when false positives and false negatives threaten an application’s effectiveness and business value — and cause product leaders and developers to mistrust the security team. An effective WAF protects the application while allowing it to serve customers as intended with minimal friction. This requires solid detection, protection of apps and APIs from a range of attacks, automated policy updates, the ability to effectively create and test new rules, and simple management and configuration features that don’t disrupt the application’s performance and efficacy. The breadth and depth of automation and integrations. All vendors offer infrastructure-as-code (IaC) integrations and APIs to help customers scale WAF deployments and management functions. But security pros will want to check that vendors fully support APIs and IaC templates and keep them up to date with new features and functions. Also, check that integrations with security operations (SecOps), development and operations (DevOps), application scanning, and vulnerability management tools are easy to implement. For SecOps tools like security incident and event management (SIEM) and security orchestration, automation, and response (SOAR), ask about granular data feed options, which help minimize data storage costs, and supported preconfigured dashboards. The vendor’s application protection platform strategy. A few years ago, most WAF solution vendors had acquired or built out adjacent solutions like API security, bot management, and client-side code protection and offered customers a portfolio of loosely coupled solutions. Today, many of these vendors are moving to turn these portfolios into true platforms with a unified management UI, shared context, and simplified pricing model. Security leaders should look at their WAF vendor’s platform strategy to see how it can grow with them and streamline their efforts in one or more adjacent categories. The Forrester Wave™: Web Application Firewall Solutions, Q1 2025, evaluates 10 of the top WAF vendors’ current offering and strategy and is available now! Forrester customers looking for a deeper dive can also set up an inquiry or guidance session. source

This week we published a new report looking at how generative AI (genAI) can bring fresh energy to an enterprise content management (ECM) program. Unlock The Potential of Your Documents With Generative AI is a call to action for content management leaders to explore new ways to engage with and exploit the value of their managed content.  Vendors in this market have been on an innovation hot streak, as evidenced in our recently published report, The Forrester Wave™: Content Platforms, Q1 2025. All evaluated vendors had genAI capabilities and roadmaps to support genAI’s ongoing evolution. Bring AI To Your Content Instead Of Bringing Your Content To AI  Enterprises with well-governed content repositories should have an unfair advantage with genAI success compared with businesses with poor content hygiene. Benefits include:  Protection of corporate content from training models. ECM vendors are adopting retrieval-augmented generation (RAG) architectures to shield internal documents and avoid copying or uploading them to external models.  Respect for existing access controls and security policies. ECM systems provide access controls and other security policies to restrict access to roles/groups. Embedded genAI from ECM providers respect these existing permission structures and ensure that users get responses to their AI queries only if they have rights.  Reduced inaccuracy with AI queries and actions grounded in context. Vendors are exposing their genAI interfaces in workspaces, folders, or search results to ground a query or prompt in a subset of the content, providing more specific responses and links to source documents.  GenAI Can Create Value Across The Content Lifecycle  Where do we even start? Customers are still in early days of adoption of genAI in the context of their content management systems. This report provides specific examples of how genAI can add value across the content lifecycle, including:  Creation and collaboration Approvals and publication Archiving and disposition Want to talk further about genAI in the context of ECM? Or looking to invest in a modern content platform? Forrester clients are encouraged to set up a guidance session or inquiry to learn more.   source

Does it seem like every article you read tells you that the pace of change is accelerating? And do you feel as though you haven’t even figured out the last change when the next one comes along? Yeah, me too. Those articles aren’t wrong. In the years between 2019 and 2023, executives reported a 183% increase in the amount of change in their organizations. Our conversations with employees at the organizations we work with suggest that they’re feeling it, too. And while it is possible that not all change is necessary, the unfortunate reality is that for the most part we can’t avoid it. If we can’t avoid it, we’re going to have to get better at it. You might have heard the well-worn stat that 70% of change initiatives fail, but this data point lacks a lot of evidence and context. (If you’re interested, Mark Hughes of the University of Brighton Business School in the UK published an incredibly well-researched article on the topic.) It turns out that it’s actually quite difficult to measure how many changes succeed or fail and to what degree, because change takes time and value is not typically immediately visible. But we do know that organizations that use a structured methodology to approach change have better outcomes. A study by Prosci found that 69% of organizations used a structured approach, and of those, 59% achieved good or excellent levels of effectiveness while just 26% of those that did not use a structured approach achieved the same levels of effectiveness. For the last two years, I’ve been talking with our clients in guidance sessions, onsite working sessions, and conferences. What I hear over and over again is that organizations have a great plan but struggle to get people to engage, to change behavior, and to embrace new processes. Frustration is high, and while a disciplined approach helps, it does not make change a friction-free process. All change involves conflict. This year, we’re bringing change to the main stage at our B2B Summit North America and CX Summit EMEA events. I will be in Phoenix at the end of this month sharing essential information for change leaders about how to navigate through increasing uncertainty and how to improve your change outcomes. Then, in early June, my amazing and talented colleague Manuel Geitz will be on stage sharing these frameworks in London. With change happening at warp speed, you’ll gain tools for envisioning, managing, and sustaining the energy needed to keep pace, so join us in Phoenix or London — we’d love to see you there! source

Change isn’t just hard — it’s a continuous battle, and one that automation will make more intense and frequent. And if you think you’re prepared for automation’s pace of change that is coming, you’re already behind. We’ve barely grown comfortable with the past few years’ changes — remote work, video calls, hybrid chaos — and that’s just the warm-up. Take note from Forrester’s Automation Survey, 2024: 82% of companies are about to invest in generative AI (genAI), which will drown out the old ways of working. And here’s the kicker: The very teams deploying AI agents are admitting they don’t know how to manage the change they’re creating. Automation teams struggle with CM (change management) and admit it’s one of the biggest challenges of adopting automation. The Common Pain Points For Automation Initiatives Our new report, Change Management: Taming The Automation Beast, breaks down the challenges that automation decision-makers face and highlights how effective change management is more crucial than ever. Our analysis revealed the following CM concerns brought on by automation projects: Proving ROI. Change management initiatives related to automation projects require investment. Securing budget for these efforts can be challenging, as business leaders need to see ROI for change management itself. Employee retention, mental state improvements, and the value of ongoing skills development are hard to quantify. Job loss. Introducing new ways of working, especially automation, brings uncertainty and fear of job loss. In Forrester’s Future Of Work Survey, 2024, 39% of global workers said they fear losing their jobs to automation in the next 10 years. According to the customer service operations manager at a large manufacturing company, “Automation is perceived as a big threat … employees are not welcoming of change, and some view automation as an opportunity to reduce headcount.” Growing skill gaps. Ensuring that employees have the necessary skills to use automation and AI technology requires ongoing training. Many organizations lack proper training programs for nontechnical employees. Only 19% of global individual employees say they have been through formal training on how to use AI for work. As many employees are being given access to AI tools/AI agents, this poses a real challenge. Confidence And Trust In Change Management Is Missing Change management has a basic problem. Top-level executives report a high degree of confidence in their CM practices, yet employees believe the opposite: CM initiatives are inadequate. Employees lack confidence in CM practices and lack trust in their organization’s leaders. What this means is simple: Folks in charge of implementing CM are not trusted to follow through on promises. Employees would like CM to be more integrated into leadership responsibilities. However, without addressing this chasm of confidence and trust, it is unlikely to work. It’s Time To Bring Your Change Management Up To Speed The accelerating pace of automation demands that traditional CM methods adapt to its speed and impact. You first need to address your organization’s AIQ (the AI quotient), which measures the readiness of individuals, teams, and organizations to adapt to, collaborate with, trust, and generate business results from genAI and other forms of AI. You then need to focus on Change Management: Taming The Automation Beast. This report highlights the following key areas for automation teams to prioritize: clear communication around pending automation, giving them more control over automation that impacts their work, and adopting an iterative and continuous CM approach. source

The UK government has declared that it will “take a ‘test and learn’ approach with spending on AI and digital to push innovation.” Staged funding, mission-driven prioritization, and outcome metrics — the civil service bringing some Silicon Valley mentality to play. In theory, I like it. In practice … hold that thought for now. The complex relationship between the UK government, big tech, transparency, and trust has been in the headlines over the last few weeks. If you’ve missed it, myself and Enza Iannopollo have been blogging almost weekly to help try to make sense of the rapidly emerging landscape. We’ve been invoking some classical and mythological imagery, and I’m drawn back to Odysseus testing and learning his way across the Aegean Islands on his voyage home from Troy. But this week, I’m jettisoning the classics for something more visceral. So to help you catch up, here’s a fast-paced 3-minute London punk playlist. Buckle up: Track 1: London Calling We started in mid-February by outlining how the UK government is ready to embrace AI; without trust, however, it risks disaster. Together with the US, the UK refused to sign an international agreement on AI at the global AI Action Summit in Paris, saying it failed to address global AI governance issues and leaves questions on national security unanswered. It simultaneously announced a partnership with Anthropic and the launch of a government AI playbook. Turn it up. Track 2: My Way As we dug further, it became apparent that, despite the UK government’s ambition to create an AI innovation hub and power public service transformation, a key part of the strategy was missing: guidelines for how to build trusted AI. While the EU AI Act clearly articulates prohibited, high, and low risk levels in AI use cases, the UK guidance shrugs its shoulders and leaves civil servants to do it their way. Track 3: Pretty Vacant Next, Apple announced that it was withdrawing Advanced Data Protection for UK users, removing end-to-end encryption of users’ data, files, photos, and messages in order to comply with the UK government’s demands to be able to access all of a user’s data (under certain circumstances). Given the low levels of trust that UK citizens have in their government compared to many other countries, this wasn’t a good look for Westminster or Apple. Track 4: I Fought The Law But then Apple decided to fight the power and took the case to an Investigatory Powers Tribunal. Ramping up its transparency play outside the UK, it also took the decision to remove or retain its diversity, equity, and inclusion (DEI) policies to its shareholders. Transparency Is At The Heart Of Trust You’d be forgiven for having missed some of these “shenanigans.” But wait: In a “death of irony” kind of moment, New Scientist applied a healthy dose of transparency last week when it used a freedom-of-information request to reveal how the UK tech secretary uses ChatGPT for policy advice — #FacePalmEmoji. Let’s focus on what’s at stake here: UK citizen trust in the government is low. A test and learn approach to delivering new AI applications means that mistakes are inevitable — it’s literally baked into the approach. When trust is high, our research shows that stakeholders are more likely to forgive mistakes. When trust is low, the impact can be dramatic. UK consumers trust Apple more than the government to keep their personal data safe. Some 35% of UK consumers trust Apple with their personal data, compared to 25% who trust the government. Further eroding its trust level with citizens by getting into battles with Big Tech over laws that reduce citizen privacy isn’t going to help the UK government build trust. Transparency is a key driver of trust. Based on our initial trust research in 2021 and 2022, customers who believed that a company was transparent were anywhere up to four times as likely to forgive its mistakes as those who believed that it wasn’t transparent. Trust isn’t a nebulous thing — it’s tangible, measurable, and quantifiable. It’s hard-won and easily lost. The UK government has a bold plan for change. These are generational missions, not projects. If this is going to work, the UK government needs citizens to trust it. We will be launching our Government Trust Index soon, in which we’ll look at the levers of trust in more detail. Stay tuned for more. source

Customer relationship management (CRM) systems initially focused on supporting core front-office functions such as sales and marketing, but the value proposition of CRM has expanded significantly through strategic tech convergence, driving substantial revenue growth for vendors. CRM moved into the middle office to enable order management and subscription billing. This expanded the platform’s utility, enabling businesses to manage the entire customer lifecycle from initial contact to post-purchase processes. Then, CRM further expanded capabilities into employee experience to support employee help desks. As CRM’s value is compounded with its tight alignment to enterprise resource planning, vendors such as Oracle and SAP started to offer connected suites and industry clouds. The impact of tech convergence has enabled vendors to increase revenue by offering a broader range of capabilities, enhance customer value with integrated platforms, strengthen market position by expanding market reach, and increase customer lock-in with a concentrated dependency on a single vendor. Up until recently, market dominance was relatively stable, and battle lines remained fairly established between vendors. Salesforce And ServiceNow Make Bold Moves Into Each Other’s Territory This all changed in 2024 when ServiceNow, a revolutionary of the IT service management (ITSM) space and leading ITSM vendor, entered the CRM market with its Sales and Order Management application. When coupled with ServiceNow’s customer service and field service application, this suite allows companies to launch, sell, fulfill, and service products on a unified platform. This combination is particularly attractive to industries such as financial services and communications. The application’s workflows cut across the front, middle, and back office in order to orchestrate work between customer operations, finance, and inventory management. This approach reduces operational errors and fulfills products faster; it also makes enterprise data more accessible. It doesn’t necessarily compete with Salesforce’s CRM head on, but it does look appealing for organizations where seamless cross-departmental coordination is paramount. ServiceNow offers a different take on CRM that may be better aligned to the needs of particular industries with complex operations. Salesforce responded to this threat by doubling down on its employee help desk offering. The vendor offers a market-leading customer service application that, when used for employees instead of customers, can be configured to be a robust employee help desk. Salesforce Service Cloud can also be used for ITSM via features such as case management, knowledge management, and incident management, though right now, it is not a dedicated ITSM platform. Yet Marc Benioff, CEO of Salesforce, hints that Salesforce is about to launch an ITSM product. This would move Salesforce right into the crown-jewel territory of ServiceNow. Why Is This Important? This potential move signals once again that the era of siloed enterprise software applications and processes is over. Enterprises must orchestrate workflows to support end-to-end customer journeys that cross departments and applications. The AI race is on. All enterprise software vendors are releasing AI agents, including Salesforce and ServiceNow. Last year, Salesforce released AI agents for the front office and just announced its newest version of Agentforce. ServiceNow, with its decades of knowledge in addressing complex enterprise workflows, has just released AI agents for CRM, HR, and IT. The vendor that is able to best unlock enterprise data for AI agents will be the one that ultimately wins. Keep an eye on this space. source

The most common reason why companies purchase sales performance management/incentive compensation management (SPM/ICM) solutions is to effectively manage the administrative costs of their compensation program. Although SPM/ICM solutions do this well, the biggest value they deliver is enabling companies to create more effective compensation plans. It is standard practice for companies to reduce the volume and complexity of compensation plans to make them more efficient to manage, but the companies that get the most from SPM/ICM solutions use their capabilities to support the complexity needed to build the best plan for each role without increasing the cost to administer each. This change has become a reality recently as new providers have deployed new and innovative approaches to enable their customers, who are focused around three key points: Empowering the administrator to support more complex use cases. Doing this reduced the need for systems integrator (SI) support. For years, companies assumed they needed to have SIs to help them deploy and maintain their SPM/ICM solutions — so much so that companies hired SIs to determine which solution they should purchase. SPM/ICM new entrants into the market have changed this and are providing options that remove or reduce the need for SI investment, reducing the total cost of ownership for SPM/ICM solutions. Those considering new solutions should include SI costs as part of the evaluation process to understand the overall potential cost savings of the solutions being evaluated. Taking customer success to the next level. My evaluation of the SPM/ICM market made it clear that not all customer success programs are created equal. Though most vendors in my evaluation provide a level of customer success, the skill level of the people in these roles varies. Reference customers consistently mentioned that SPM/ICM solution providers with customer success teams dedicated to this technology provided better service than larger providers with customer success managers that support a broader portfolio. When deciding on the best solution, validate the skill set and focus of support resources. Continuing to receive value from foundational capabilities. When talking to vendors, we found that generative AI (genAI), scenario planning, and CRM integrations are often differentiators, but very few reference customers have deployed these features. Although a handful of evaluated vendors have genAI capabilities, reference customers didn’t notice, and those whose solutions had these capabilities weren’t using them. Though these capabilities will be more useful in the future, the most valuable capabilities of SPM/ICM solutions today are core features such as ease of use, the ability to handle complex calculations, and data transformation. Don’t get distracted looking at the cool features; instead, focus on the solution’s ability to execute core compensation use cases. Seeing what modern SPM/ICM providers have been able to do to add value with foundational capabilities is exciting. The solution is modernizing both from a technology and support standpoint and achieving strong results. While genAI capabilities are just starting to emerge, providers in this category are well positioned to continue to evolve and improve their capabilities with AI. Those evaluating these solutions should start looking beyond the standard cost-savings metrics and toward ways to leverage their core capabilities to optimize plan effectiveness. To learn more about the SPM/ICM category and its vendors, you can read the latest landscape report and Forrester Wave™ evaluation. source

AI’s Escalating Demands On Data Centers Rapidly progressing AI initiatives coupled with new sustainability regulations have sparked increasing demand for computing power, distribution, and technology capabilities in data centers. Tech leaders are addressing these computing power demands by turning to advancements such as new cooling methods, semiconductors, power sources, digital twins, and internet-of-things (IoT) monitoring capabilities. In light of these advancements and increasing demand from data centers, tech leaders are reassessing their data centers and looking to implement innovative approaches to meet power demands and sustainability goals. The Transformative Potential Of Microgrids One innovation gaining momentum to address increasing data center energy demands is the emergence of microgrids. Microgrids are local power systems that use renewable energy integration to allow for reliable and resilient energy operations. Accordingly, this allows organizations to meet their sustainability goals and can help reduce energy costs. Optimized energy utilization: Microgrids facilitate the integration of various distributed energy resources (DERs) — e.g., solar, wind, and combined heat and power systems — to optimize clean energy supply, distribution, and efficiency, as well as reduce energy waste. Since microgrids are localized, they ensure that generated energy is utilized more efficiently, along with reducing transmission and distribution losses that are inevitable in traditional energy systems. Sustainability and cost-savings: Through the integration of DERs, microgrids lower reliance on fossil fuels and decrease greenhouse gas emissions, ultimately contributing to sustainable energy goals. Additionally, harnessing the use of renewable energy sources can help reduce energy costs by avoiding peak electricity prices and lowering the constant dependency on the traditional power grid. Enhanced reliability: Microgrids can operate both with the main data center power grid and autonomously, which enhances reliability by reducing the risk of outages and ensuring uninterrupted operations. The ability for microgrids to act autonomously allows for maintenance of continuous power to the localized area in the event of an outage, such as natural disasters or cyber attacks. This is critical infrastructure for services that require uninterrupted power supply. Microgrids have already been adopted by numerous organizations, including The Home Depot, JFK Airport, Southern California Gas Company, Kaiser Permanente Richmond Medical Center, and the University of California San Diego, all of which are paving the way toward a more sustainable and resilient energy future. This Is Just The Start The implementation of microgrids is one innovation that organizations are turning toward to meet power demands, improve resiliency, and move closer to a more sustainable future. Alongside microgrids, we have identified and discussed nine additional emerging innovations in the data center in our new report, Top 10 Emerging Innovations In The Data Center, 2025. This report dives deeper into innovations in types of cooling methods, semiconductors, power sources, digital twins, and IoT monitoring to meet changes in power demands, cooling needs, sustainability reporting, technology capabilities, local regulations, and performance requirements. For in-depth insights into AI’s impact, data center trends, and sustainability strategies, Forrester clients can access our exclusive reports and set up guidance sessions to continue to explore current trends and solutions. source