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Forbes
4 days ago
- Business
- Forbes
Measuring AI's Impact And Value: 20 Essential Factors To Consider
getty As AI systems become more embedded in core business functions, traditional metrics like precision and recall capture only part of the picture. Measuring ROI now requires a holistic lens—one that accounts for AI's impact on workflows, decision-making speed and long-term adaptability. Whether a business is assessing its internal AI tools or the AI-powered features included in its products, relying solely on technical benchmarks can result in missing or misinterpreting the broader value—or potential risk—AI systems introduce. Below, members of Forbes Technology Council highlight key factors worth considering when assessing AI success and ROI, explaining why each one offers a more complete view of performance. 1. Hours Reclaimed A practical metric I use to measure AI's ROI is hours reclaimed. I recently rebuilt our GTM messaging across three segments—what previously took 20 hours to do manually, I completed in two, and then in 45 minutes using AI. That time saved is measurable, repeatable and directly tied to productivity gains, reduced errors and faster execution across teams. - Farrukh Mahboob, PackageX 2. Decision Latency Reduction Decision latency reduction is a powerful AI success metric. It measures how quickly AI enables smart, confident decisions, compressing the time between insight and action. Unlike cost savings, this reflects real strategic agility. When decisions speed up, it shows AI is truly embedded in how the business moves. - Jason Missildine, Intentional Intensity Forbes Technology Council is an invitation-only community for world-class CIOs, CTOs and technology executives. Do I qualify? 3. CO2 Usage A metric recently brought into the measurement equation is CO2 usage. Along with tracking more traditional efficiency metrics that showcase faster or cheaper results thanks to an AI system, calculating how much energy it uses provides an offset figure that can be incorporated into evaluations and influence longer-term strategy. - Mark Thirlwell, BSI Group 4. Ethical Outcomes One powerful metric is how well AI systems translate human values into safe, bias-free outcomes that benefit society and stakeholders. More than delivering correct answers, AI systems need to model responsible behaviors, which in turn leads to growth, innovation and a better customer experience. - Vishal Talwar, Wipro Ltd. 5. Contextual Adaptation Quotient Contextual adaptation quotient is a powerful new metric that measures how well AI systems sustain performance across varying domains, users or conditions without retraining. Unlike static accuracy scores, CAQ captures real-world adaptability, highlighting robustness, transferability and long-term ROI in dynamic environments. - Nikhil Jain, SmartThings, Inc. 6. 'Trust Delta' One insightful metric is the 'trust delta,' or how much more (or less) people trust your system after you add AI. You can measure this through user feedback and behavior changes. The smartest AI is useless if people won't use it. If your AI makes people second-guess themselves or feel uneasy, it's actually slowing them down. The trust delta shows whether you're building something people want to work with or work around. - Kehinde Fawumi, Amazon 7. Time To Confidence A genuinely insightful ROI metric for AI systems is time to confidence—how quickly a user reaches a decision they trust. In high-stakes fields like investing, speed alone isn't enough; decisions must also be defensible. - Mike Conover, Brightwave 8. Innovation Rate In my view, the innovation rate metric stands out above all. This tracks the number of new products, services or process improvements directly enabled by AI-driven insights. While ROI focuses on optimizing the present, this metric reveals how effectively AI is building a company's future. A high innovation rate proves AI is not just a cost center, but a strategic engine for growth and market leadership. - Mohan Mannava, Texas Health 9. Autonomy-To-Intervention Ratio A cutting-edge metric is the autonomy-to-intervention ratio, which tracks how long an AI system can operate before needing human correction. It moves beyond traditional KPIs like precision to reveal trust, scalability and operational ROI in real terms. A high AIR means AI isn't just working; it's learning, adapting and truly offloading cognitive burden. - Nicola Sfondrini, PWC 10. Time To Insight Reduction One emerging and insightful metric is time to insight reduction, which is how much more quickly actionable intelligence is derived from data. It reflects the AI system's real-world impact on decision velocity, efficiency and responsiveness, making it a powerful indicator of true ROI beyond cost savings or accuracy alone. - Hrushikesh Deshmukh, Fannie Mae 11. Decision Outcome Improvement The true measure of AI isn't just technical performance, but its real-world impact. Decision outcome improvement quantifies the tangible uplift in valuable results achieved when AI influences a decision, versus the baseline without it. This metric is crucial because it cuts through tech specs to show the practical, profitable difference AI makes, revealing its true ROI where it matters most. - Raghu Para, Ford Motor Company 12. Revenue Per AI Decision Revenue per AI decision is a metric that I find myself looking at quite often. It shows how well an AI system drives actual business outcomes. At our company, if an AI model suggests a payment plan and it closes faster or with higher value, that's measurable success. It ties AI performance directly to bottom-line impact, which matters more than model accuracy or usage stats alone. - Ashish Srimal, Ratio 13. Time To Value Realization One insightful metric is time to value realization, which measures how quickly a company can start deriving business value from an AI implementation. A shorter TTVR indicates efficient deployment, effective user adoption and that the AI is solving a real problem quickly, directly correlating to faster benefits and competitive advantage. - Ambika Saklani Bhardwaj, Walmart Inc. 14. Adaptive Learning Rate One unique metric for measuring AI success is adaptive learning rate, which helps quantify the speed at which an AI system can learn from new data. For instance, in audio processing, a high ALR means an AI can quickly adapt to new accents or background noises, continuously improving without constant retraining. This shows an AI's true long-term value, beyond initial deployment. - Harshal Shah 15. Autonomous Resolution Rate A powerful new metric is autonomous resolution rate, which is the percentage of tasks completed end-to-end by AI agents without human intervention. In ERP/CRM, ARR reflects true ROI by measuring how effectively AI agents handle processes like order creation, invoice matching or case resolution. High ARR signals reduced operational costs, improved efficiency and successful agent adoption at scale. - Giridhar Raj Singh Chowhan, Microsoft 16. Model Utilization Rate One enlightening measure is the model utilization rate—the percentage of the output of an AI model that gets used for decision-making or operations. It's instructive because accuracy is of no consequence if the truths are not acted on. It's a measure of real-world application and trust in AI that demonstrates the relevance and value it has in business. - Saket Chaudhari, TriNet Inc. 17. Feature Abandonment Recovery Feature abandonment recovery is the percentage of users who return to an AI feature after experiencing initial frustration. Most metrics show first-touch success, but this shows resilience. If users give your AI a second chance after it fails them, you've built something valuable. It indicates your AI provides enough value that users forgive mistakes—the ultimate sign of product-market fit. - Marc Fischer, Dogtown Media LLC 18. Resource Efficiency Index The resource efficiency index measures how well AI saves time, effort and resources by reducing manual work and enhancing productivity. Unlike traditional ROI, REI captures indirect benefits such as innovation and agility, providing a holistic view of AI's impact on workforce efficiency and strategic value in modern business operations. - Dileep Rai, Hachette Book Group 19. Access Management Data Access management data provides powerful, real-time metrics that analyze the impact and adoption of technologies and digital systems, such as those using AI. This data offers actionable insights into how tools are being used and their effect on productivity. By mapping usage trends to business outcomes, organizations can identify gaps, optimize training and prove ROI. - Fran Rosch, Imprivata 20. Return On Disruption One novel metric is return on disruption, which measures how AI redefines workflows or business models, not just cost or revenue gains. ROD captures transformative impact, signaling true innovation and long-term competitive advantage rather than incremental efficiency. - Lori Schafer, Digital Wave Technology
Yahoo
5 days ago
- Business
- Yahoo
ZoomInfo Extends Open Environment to Unlock Seamless High-Quality Data Integration
Brings ZoomInfo's intelligence to growing ecosystem of partners for more complete AI-enabled GTM motions VANCOUVER, Wash., July 24, 2025--(BUSINESS WIRE)--ZoomInfo (NASDAQ: GTM), the leading Go-To-Market (GTM) Intelligence Platform, today announced it is adding API Access to all ZoomInfo Copilot plans. This allows customers to access ZoomInfo's leading AI-ready market intelligence data layer across a growing ecosystem of partner applications. "Data powers the GTM flywheel, and AI is what propels it into overdrive," said Ali Sadat, Senior Vice President of Product Management at ZoomInfo. "Speed alone means nothing without precision—without the right data, even the fastest motion leads nowhere. By offering ZoomInfo customers access to our data via partners, we're enabling their applications to deliver clean, enriched data from the start—fueling smarter AI, sales, marketing, and operational strategies." Benefits of ZoomInfo's APIs:Plug-and-play access to ZoomInfo data from ISV's, including Salesloft and Outreach functionality where ZoomInfo customers can discover key contacts not in their CRM and ensure contacts have working email and phone Functionality and Data – As new insights and datasets are added, ISVs can easily join these attributes to Contacts and Companies using ZoomInfo IDs. Partners and customers can leverage APIs through ZoomInfo's GTM Intelligence platform. All ZoomInfo Copilot customers now have APIs included in their plans which allow them to build private API apps or connect to ZoomInfo's growing ecosystem of partner integrations. Initial partners include Outreach and Salesloft, who are augmenting CRM data with additional context directly from ZoomInfo. For information about purchasing or upgrading to ZoomInfo Copilot or becoming a partner click the link. About ZoomInfoZoomInfo (Nasdaq: GTM) is the Go-To-Market Intelligence Platform that empowers businesses to grow faster with AI-ready insights, trusted data, and advanced automation. Its solutions provide more than 35,000 companies worldwide with a complete view of their customers, making every seller their best seller. ZoomInfo is a recognized leader in data privacy, with industry-leading GDPR and CCPA compliance and numerous data security and privacy certifications. For more information about how ZoomInfo can help businesses with go-to-market intelligence that accelerates revenue growth, please visit View source version on Contacts Media Contact Silvie CasanovaCorporate CommunicationsZoomInfopr@
Business Wire
5 days ago
- Business
- Business Wire
ZoomInfo Extends Open Environment to Unlock Seamless High-Quality Data Integration
VANCOUVER, Wash.--(BUSINESS WIRE)--ZoomInfo (NASDAQ: GTM), the leading Go-To-Market (GTM) Intelligence Platform, today announced it is adding API Access to all ZoomInfo Copilot plans. This allows customers to access ZoomInfo's leading AI-ready market intelligence data layer across a growing ecosystem of partner applications. Partners and customers can leverage APIs through ZoomInfo's GTM Intelligence platform. Share 'Data powers the GTM flywheel, and AI is what propels it into overdrive,' said Ali Sadat, Senior Vice President of Product Management at ZoomInfo. 'Speed alone means nothing without precision—without the right data, even the fastest motion leads nowhere. By offering ZoomInfo customers access to our data via partners, we're enabling their applications to deliver clean, enriched data from the start—fueling smarter AI, sales, marketing, and operational strategies.' Benefits of ZoomInfo's APIs: Plug-and-play access to ZoomInfo data from ISV's, including Salesloft and Outreach functionality where ZoomInfo customers can discover key contacts not in their CRM and ensure contacts have working email and phone numbers. Expanding Functionality and Data – As new insights and datasets are added, ISVs can easily join these attributes to Contacts and Companies using ZoomInfo IDs. Partners and customers can leverage APIs through ZoomInfo's GTM Intelligence platform. All ZoomInfo Copilot customers now have APIs included in their plans which allow them to build private API apps or connect to ZoomInfo's growing ecosystem of partner integrations. Initial partners include Outreach and Salesloft, who are augmenting CRM data with additional context directly from ZoomInfo. For information about purchasing or upgrading to ZoomInfo Copilot or becoming a partner click the link. About ZoomInfo ZoomInfo (Nasdaq: GTM) is the Go-To-Market Intelligence Platform that empowers businesses to grow faster with AI-ready insights, trusted data, and advanced automation. Its solutions provide more than 35,000 companies worldwide with a complete view of their customers, making every seller their best seller. ZoomInfo is a recognized leader in data privacy, with industry-leading GDPR and CCPA compliance and numerous data security and privacy certifications. For more information about how ZoomInfo can help businesses with go-to-market intelligence that accelerates revenue growth, please visit
Forbes
5 days ago
- Business
- Forbes
A Fintech Go-To-Market Shift: Preparing For Enterprise Sales
Jayant Walia is Head of Business Development and GTM at Gainbridge, an insurtech revolutionizing the insurance & retirement industry. At some point in their journey, every ambitious B2B fintech company has to wrestle with this question: Do we keep selling to other tech-forward startups, or do we go after the whales—the banks, insurers and legacy platforms with the biggest budgets and deepest moats? I've seen this play out countless times. Teams start by selling to fellow builders—fast-moving companies that love APIs, skip SOC 2 on day one and are eager to co-create. Why? Because selling to other startups is faster, cleaner and way more gratifying when you're chasing early momentum and trying to prove something. But here's the pattern: Those same companies—if they survive long enough—eventually start inching toward banks and large financial institutions. It doesn't happen all at once, but it always happens because that's where the real money is. And that's also when the pain starts. Why It's Hard To Sell To Legacy Financial Institutions Banks and large insurers are some of the toughest customers you'll ever chase. They move slowly, scrutinize everything and are not impressed by your slick user interface or recent funding. They've been burned before by outages, compliance failures and integrations gone sideways, and they don't forget. They also carry tech debt, meaning decades of layered systems patched over rather than rebuilt, making integration risky and complex. When something breaks, it can become a board-level crisis. But once you're in, you become core infrastructure rather than an experiment. Yet that's the market that keeps so many fintechs up at night—because once you're in, you're in. These aren't transactional customers. You become part of the foundation. You're no longer the experimental layer—you're the infrastructure. Startups Love Startups (Until They Don't) It makes total sense that early fintechs target other startups. The sales cycles are shorter. The buyers are more technical. The value proposition is clearer. You can show up with a working demo and close in a few weeks. This approach builds momentum and excites investors. You get to show logos, annual recurring revenue growth and product adoption in a short time. But there's a ceiling to this model. Your customers are often burning venture capitalist money. Their own stability is shaky. You might spend months onboarding someone just to see them pivot or fold. And before you know it, 80% of your revenue is tied to companies with the same Series B pressure you have. Enterprise Sales Are A Different Beast This is where things get real. The shift to selling to banks, insurance carriers or institutional platforms doesn't just require patience. It requires a full reset on how your company operates. Let's start with the sales team. If your account executives have been closing fast deals with founders and product leads, they're probably not going to enjoy a nine-month sales cycle filled with procurement hurdles, security reviews and six-person buying committees. They may get frustrated or worse, churn. To avoid this, you need to guide your sales teams into an enterprise mindset. Providing enterprise sales training, bringing in mentors with large financial institution experience and re-evaluating which representatives can adapt to longer cycles are all essential steps. Adding respected advisors or former bank executives further signals credibility and opens doors. As trust builds with large clients, testimonials will naturally follow and accelerate future deals. Then there is compensation. You cannot keep using a pure SaaS quota system. These deals are whale hunts. You might close one or two a year, but they can transform your business. You'll need to shift incentives toward relationship depth and pipeline quality. You'll need higher base salaries, slower variable payouts and quotas built for fewer but larger wins. Even your product road map has to mature. It's no longer about just shipping the next feature. It's about proving you won't break under pressure, and that you're scalable, supportable and audit-friendly. It's about proving that you're not just a startup but a strategic partner. You demonstrate this by earning enterprise-level certifications, building real disaster recovery plans, publishing clear uptime commitments and undergoing independent security assessments. What You Get In Return Once you successfully reset, it's game-changing: • Your revenue stabilizes. • Churn drops dramatically. • Your margins improve, especially on fee-based models. • You stop obsessing over month-to-month cash flow swings. • VCs see a more predictable, defensible business model. • Most importantly, you're in the room with decision makers who manage billions, not millions. Now AI Enters The Chat We're seeing this all over again with the rise of AI in fintech startups. Many are building powerful tools—fraud detection, risk scoring, agent-based onboarding—and again, selling to other startups because it's easier. But we know where this ends: The real opportunity is with the legacy players. The problem? It's hard to flip the switch later. Selling to large financial institutions isn't an easy pivot; it should be a foundational strategy you bake in early, even if you don't activate it on day one. That means aligning hiring, go-to-market strategy and product development with the long-term vision of serving enterprises so you don't have to scramble for credibility later. Final Thought Selling to legacy financial institutions is not for the faint of heart. It's slow, political and demands the long game. But if you want something that survives cycles and builds true enterprise value, it's a move worth making. Don't wait until you're desperate. The sooner you align your team, your road map and your strategy in that direction, the more likely it is that you'll make it and stay there. Opinions expressed here belong solely to the author and do not necessarily reflect the views of their employer. Forbes Business Development Council is an invitation-only community for sales and biz dev executives. Do I qualify?
Forbes
5 days ago
- Business
- Forbes
Breaking The Mold: How To Become A Transformational CMO, Part 1
Meghan Keough, Chief Marketing Officer, C1. The chief marketing officer (CMO) is no longer just the voice of the brand. Or at least, we shouldn't be. Today's CMO should be the driving force behind business transformation—influencing how companies position themselves, go to market, adopt technology and serve customers. CMOs are uniquely positioned to lead this change. We sit at the intersection of product, positioning, sales, voice of the customer, market insights, competitive intelligence, experience design, storytelling and data. We understand the market, the buyer and the story that connects the two. Yet too often, marketing is relegated to a cost center, boxed out of the strategy room. But with the most comprehensive view of the business, marketing is often best positioned to lead transformational growth. Throughout my career, I've led brand overhauls, go-to-market (GTM) pivots and platform reinventions. What I've seen is this: When marketing is brought to the front of the transformation agenda, the business moves faster, aligns better and grows smarter—all leading to increased revenue and overall growth. Five Keys To Making Marketing A Transformation Engine Too often, marketing is seen as merely 'serving' other functions through the stories we tell. But the stories we tell—and the people we tell them to—won't matter if there isn't near-perfect alignment with product strategy, customer journey design, partner ecosystems and digital operations. Transformation starts when marketing breaks out of its silo. At 8x8, for example, I saw the need to reposition our solutions from point applications to a platform—but I didn't own the roadmap. To drive change, I had to build credibility with product and sales through market data and customer insight. Influence precedes impact. CMOs can't transform anything alone. We must lead across functions, shaping a common understanding of what's next in the market, the roadmap and customer demand. This requires listening widely, connecting dots others don't and making the complex feel simple. To achieve this, I've leaned into a leadership style shaped in part by being a middle child. I listen, facilitate and build bridges. It's served me well, especially as the pace of change accelerates. We hear a lot about AI, automation and the power of a modern martech stack. However, none of that works without the right people and processes in place. Think of the buying journey as a manufacturing line for commercial outcomes. Along the way, we must be deliberate about the conversion of the opportunity, with technology facilitating the buyer and seller journey, not complicating it. Whether marketing drives most of the pipeline or just part of it, at a point in the process, a business development team has to be engaged to convert interest to intent. Once we have established the right process, then the right technology makes these teams and data more connected, relevant, responsive and successful—and enables the organization to make the most of the martech stack. It's not revolutionary, but too often it's overlooked. Customers aren't just references. They should also be your strongest signals when making trade-offs and determining the viability of new ideas. I've built voice-of-the-customer-like engagements, including customer reference and advocacy programs, from the ground up multiple times in my career, and going back to my early technology consulting days, I am a firm believer in working closely with customers. This takes many forms, such as advisory boards and customer summits, and experience has taught me that this input can sharpen your product roadmap and positioning, accelerate deals and improve conversions. The transformation-ready CMO can't be defined by any one specialty. We're strategists, technologists, storytellers and people leaders, often all at once. Early in my career, I moved between roles that didn't squarely fall within marketing: I started as a technology consultant, led product management and marketing at a startup and later took on an alliance role to move closer to sales. It looked nonlinear, but it built the foundation for how I lead today. I don't just run campaigns. I drive business. If you're building your marketing career today, don't just go deep. Go wide. Step into product. Learn partnerships. Get close to the tech. These aren't detours. They're preparing you to lead. Marketing today is more complex than ever. But complexity isn't a burden—it's our opportunity. The CMO has never been better positioned to drive change. In my next post, I'll explore strategies CMOs can use to develop their ability to lead a transformation, and in future posts, I'll expand on some of the topics I've laid out here and take up other key topics, such as the CMO as system integrator to business innovator, the new AI-powered content supply chain and turning the voice of the customer into a competitive advantage. Forbes Communications Council is an invitation-only community for executives in successful public relations, media strategy, creative and advertising agencies. Do I qualify?
