> **来源：[研报客](https://pc.yanbaoke.cn)** First Edition # Trends in Technology Insights and trends from 450 tech leaders worldwide. # Executive Letter The technology industry is navigating a period of significant macroeconomic pressures and growth challenges, with $55\%$ of tech companies expecting to miss their revenue goals. A clear trend is emerging: AI is central to navigating complexities and driving our future success. An overwhelming $90 \%$ of tech leaders agree AI is vital for delivering on key priorities. A majority of AI’s impact lies in the front office. It is actively being leveraged to increase employee productivity, reduce operating costs, and unlock new revenue streams. The generative AI market alone is projected to reach an astounding $1.3 trillion over the next decade, promising an additional $280 billion in new software revenue. Investing in AI, especially agentic AI, is paramount for product innovation, customer experience enhancement, and growth at scale. We must act decisively to define our AI strategies and harness this transformative power. # Lenore Lang Lenore Lang EVP, Technology, Media, and Telecommunications Sales # What You'll Find in This Report For the first edition of the “Trends in Technology” report, Salesforce surveyed 450 tech industry professionals, including C-suite executives, founders, senior vice presidents, directors, and more, to learn more about: - Industry priorities and reactions to current macroeconomic factors - Why diversification of revenue streams, particularly toward more consumption-based models, is top of mind - How tech organizations are adapting to rising customer expectations - How tech leaders are thinking about agentic AI and the challenges they're facing when it comes to implementation Due to rounding, not all percentage totals in this report sum to $100\%$ . All comparison calculations are made from total numbers (not rounded numbers). Data in this report is from an anonymous survey conducted from April 28, 2025 through May 13, 2025. Respondents represent 30 countries across 6 continents. All respondents are third-party panelists. For further survey demographics, see page 27. Australia Ireland Portugal Brazil Israel Singapore Canada Italy Spain Denmark† Japan Sweden† France Mexico Switzerland Finland† Netherlands United Kingdom Germany Norway† United States India New Zealand # 450 tech leaders surveyed worldwide †Single Sample Group Flag icons: Getty Images # Contents Executive Summary 05 Chapter 1: Priorities and Challenges 06 Chapter 2: A The Revenue Remix: The Industry Response to Growth Challenges. 11 Chapter 3: Happy Customers, Healthy Growth: Customer Experience Drives Revenue . 16 Chapter 4: The Agentic Era Has Arrived 20 Look Ahead 24 Explore More Technology Resources 25 Survey Demographics 26 # Executive Summary Reset. Rethink. Results. AI, customer experience, and the revenue remix are driving the next era of tech industry growth and innovation. Macroeconomic pressures and increased competition have ignited a renewed focus on growth and differentiation through product innovation throughout the tech industry. Tech leaders are looking to AI as a way to help their organizations achieve these goals. They hope that these tools, alongside new revenue models that help offset the costs of product development, will help them unlock efficiency, boost productivity, and deliver the next-level customer experiences that today's market demands. # 01 Priorities and Challenges Industry leaders are prioritizing growth and innovation in the midst of uncertain macroeconomic circumstances. Many are hoping AI is the key to unlocking efficiencies, increasing revenue, and staying ahead of the competition. $90 \%$ of tech leaders agree AI is must when it comes to delivering on their priorities. # The Revenue Remix: The Industry Response to Growth Challenges Economic instability and increased competition have tech leaders looking toward new revenue models, particularly consumption-based, in hopes that it will help drive revenue and combat the increased price of building AI capabilities into their products. $72 \%$ of tech companies have more than one revenue stream, with high performers adopting new revenue streams at a faster rate. # 03 Happy Customers, Healthy Growth: Customer Experience Drives Revenue Rising customer expectations are creating challenges for tech companies that already struggle when it comes to balancing investments in product innovation with delivering a great customer experience. $34 \%$ of tech companies saw stagnant or decreasing net revenue retention (NRR) year over year. # 04 The Agentic Era Has Arrived Tech leaders recognize the value of AI and are eager to implement AI capabilities, but many face challenges when it comes to data quality, AI implementation, and a strong AI strategy. Only $45 \%$ of companies have a clearly defined AI strategy. # 1 # Priorities and Challenges # Tech Leaders are Optimistic Amid an Uncertain Economy Tech industry leaders came into 2025 feeling confident that the instability of the past few years was coming to a close. Even so, today's tech industry remains wary, demonstrating far more cautiousness than the move-fast-and break-things industry of the past. Macroeconomic issues like inflation, high interest rates, and tariff uncertainty are forcing the industry to operate without the influx of VC investments or the runaway spending mentality of the past. This uncertainty around current economic policies has the industry worried about both a near and distant future. This is especially true for hardware and semiconductor companies, for whom tariffs pose a greater, more immediate concern. However, despite these macroeconomic challenges, most tech leaders report feeling positive about the overall state of the industry. # Economic Pressures Suggest the Industry's Healthy Outlook May Be Short-Lived The majority of tech leaders feel optimistic about the state of the industry # Top business challenges 1 Changing customer needs / expectations 2 Competition with other businesses 3 Macroeconomic conditions 4 Disconnected data sources 5 Implementing / expanding implementation of artificial intelligence # Efficient Growth and Product Innovation Drive Differentiation Today's tech leaders have moved away from a growth-at-all-costs mindset, focusing instead on efficient growth and differentiation through product innovation. While the focus on growth isn't new, the circumstances around it have changed. Economic uncertainty and increased investor scrutiny have made the industry more cautious - especially around spending. As a result, leaders are looking to find efficiencies that might reduce costs and increase productivity in hopes that this will free up resources for innovation and allow them to remain competitive. Many are betting on AI to help strike that balance. Investments in Data, Security, and AI Align with Goals for Growth, Innovation, and Efficiency Tech industry leaders' top priorities 1 Driving revenue growth 2 Product innovation 3 Improving the customer experience 4 Reducing costs 5 Increasing employee productivity AI is a must have for every business priority Very important Somewhat important Neutral 0% Somewhat unimportant 0% Very unimportant # 01 # AI is the Engine Behind Industry Priorities Tech leaders' investments in AI demonstrate a belief that the technology will allow them to achieve their priorities and combat current challenges. So much so that investments in AI and implementation mark the industry's greatest area of investment after product development and innovation. The vast majority of tech companies are already using AI in their day-to-day operations, with more than a third having already implemented agentic AI capabilities – and those who haven’t say they plan to do so in the near future. This aligns with tech leaders' belief that AI is critical to their ability to improve productivity, ensure data accuracy, provide better experiences, generate more revenue across more streams, and reduce overall operating costs. # The Time for AI – Particularly Agentic AI – Is Now Financial and resource investments over the next 12 months Substantially Increase Increase Decrease Substantially decrease Product development/ innovation Sourcing/ implementing AI tools Headcount Improving data quality ${13}/{14}$ 73% Mergers & acquisitions 13% 56% 26% Pre-IPO readiness 7% ${13}/{14}$ ${12}/{12}$ ${12}/{14}$ 549 3% Data security AI is the norm across the tech industry Currently Using Planning to Use No Plans to Use Predictive AI Generative AI Agentic AI 34% 58% 7% # Spotlight: # Impact of Tariffs on Hardware and Semiconductor Companies Unlike the broader tech industry, hardware and semiconductor companies feel less confident about their near-term economic performance. The physical, global, and cost-intensive nature of their products ties their success more closely to global circumstances and macroeconomic forces. This is evidenced by the fact that geopolitical instability, conflict, and inadequate tools and technology rank among their top five challenges. In response, many are shifting strategy – prioritizing agility and cost-reduction over straight-up growth. When it comes to AI, $97\%$ of these organizations are either already using or planning to use agentic AI. Agentic AI automates complexity and makes a huge difference in the ability to pivot and respond more quickly in the face of disruption. Agents can be used to monitor supply chain disruptions, uncover sourcing alternatives, reroute logistics, adjust forecasts, identify cost-saving opportunities, and proactively flag issues across partners and channels. # Hardware and Semiconductor Companies Face Increased Pressure Due to Macroeconomic Circumstances Hardware and semiconductor company expectations for performance trail those of the greater industry Extent to which tariffs are driving a shift in business strategy Implementing price protection/ pricing approvals Reducing costs/spend Adjusting pricing strategy Diversifying supply chain Pausing large-spend decisions Reducing investment in product innovation Not applicable # 2 # The Revenue Remix: The Industry Response to Growth Challenges # 02 # Growth Is Hampered by Inefficiency Despite coming into 2025 with an optimistic outlook, the reality of a competitive environment alongside economic uncertainty is starting to take hold. Fifty-five percent of tech companies expect to miss this year's revenue target and $65 \%$ of sales reps expect to miss their sales quotas. While some of this could be blamed on economic factors, it may also be the result of inefficient operations. Many companies have yet to implement solutions that would allow teams and associates to trade manual work for more high-value activities. Case in point? Today's sales reps only spend $30\%$ of their time actually selling; $54\%$ of their time is spent on administrative tasks. With agentic AI, these teams could hand off tasks like lead prioritization, generating quotas, and meeting preparation to agents, allowing them to focus more time on actually selling. # Cost of Inefficiency: Missed Targets and Misused Talent Majority of tech companies expect to miss their revenue target this year 21% More than 100% of revenue target 22% 100% of revenue target 28% 90-99% of revenue target 17% 8% 80-89% of revenue target 70-79% of revenue target 3% Below $69\%$ of revenue target 2% Don't know How sales reps spend an average work week Source: State of Sales, 6th Edition # Profit Pressures Drive Diversified Revenue Streams The industry's drive for innovation and differentiation is changing how value is delivered, monetized, and sustained. Investments in AI are expensive, with many tech companies trying to allay these costs by finding revenue streams beyond the traditional license or subscription model. At present, there is still work to be done. Nearly one third of companies still report only having one revenue stream. However while traditional models still reign supreme, other models are gaining steam – and rightly so. Companies that are exceeding their revenue targets are adopting new revenue streams at a faster rate, with $72 \%$ utilizing more than one revenue stream. # The Industry Approach to Revenue Models Is Shifting Revenue models currently used across the tech companies Revenue diversification is becoming the norm # High Performers Are Expanding Sales Channels Beyond just revenue streams, many high-performing tech companies are also broadening the channels they sell through. Diversified channel sales often equate to broader reach, reduced risk, and scalable growth. At present, channel sales and resellers make up a significant portion of the sales force at tech companies, with marketplaces continuing to grow – especially among high performers (those hitting their revenue targets). This is likely because selling through channel partners allows companies to scale more efficiently, driving growth without the added burden of expanding internal headcount or overhead like direct sales would require. # Channel Check: More Channels = More Growth Channels through which tech companies are selling their products and services Low performers are over indexing on direct sales Low performers are using marketplaces $28 \%$ less than high performers # Spotlight: Shift to Consumption Consumption-based models are on the rise, with both consumers and organizations viewing them as beneficial. These models lower the barrier of entry for consumers, providing a way for them to get the flexibility and transparency they desire when it comes to pricing and usage. From the tech company point of view, many are hoping a shift to consumption-based pricing will enable them to generate revenue long past the time of sale. This would help offset the increased costs of delivering AI capabilities within their products and organizational operation. Despite the rapid increase, consumption-based models are not without their challenges. They require more attention to customer experience, lifecycle management, and personalization and pose challenges when it comes to forecasting. However, many are hoping automation and agentic AI might be able to help solve these challenges. # Consumption-Based Models Are on the Rise 43% of consumers prefer consumption-based pricing Source: IDC, The Evolution of Saas Pricing Models and Growing Buyer Demand for Consumption-Based Pricing, 2025 Despite rapid increases in adoption, these models are not without their challenges Adoption of Consumption Models 1Source: Source: High Alpha, 2024 SaaS Benchmarks Report 2Source: Zylo, 2025 SaaS Management Index. # 3 # Happy Customers, Healthy Growth: Customer Experience Drives Revenue # Agentforce Can your solution integrate with our current systems? Yes, our platform integrates seamlessly with Snowflake, Databricks, and others. You can explore details in the Integration Hub. That's great. Can I see how it works in practice? Of course. I can schedule a quick demo for you. Would you like me to generate a quick guide so your team can review the steps? # Customer Expectations Continue to Rise As technology advances, customer expectations for personalization and curated service continue to rise. This puts pressure on tech companies to keep leveling their customer experience, which can be challenging to do without also increasing costs, headcount, or time. This is an area where investments in AI start to pay off. At present, service representatives are spending most of their time on routine cases that could be automated or handled by agents. This leaves them less time to deal with more complex cases, thereby impacting the customer experience. However, automating these cases so that they can be handled by AI agents could help fix the problem, increasing both efficiency and customer satisfaction. # Tech Service Professionals Face Growing Pressure to Deliver More Tech service professionals who say the following # 80% of customer expectations are higher than they used to be.\* # 75% of customers expect a more personal touch than they used to.\* # 59% say there are extensive opportunities to build relationships with customers.† *Respondents: tech leaders +Respondents: tech service reps Highly complex cases Moderately complex cases Routine cases Source: State of Service 7th Edition # Price Reigns Supreme, But Not by Much Inflation and economic instability have put costs front and center for organizations and consumers alike. When asked what made them stop buying from a company, both consumers and business buyers cited rising prices as a primary reason. That said, poor customer experience, inconsistent product or service, and inconvenience were not far behind. This indicates that while price is important, it's not the only factor. In order to keep customers beyond the first sale, tech companies might look toward adopting a more holistic approach to customer experience that addresses the vast array of customer wants, needs, and expectations. # Customers Value Price, Service, and Convenience Reasons why customers stop buying from a brand Customers generally agree that # It’s Time for a Renewed Focus on Net Revenue Retention Over a third of tech companies report stagnant or declining net revenue retention (NRR). Unsurprisingly, those with stronger performance reported better NRR – highlighting a clear connection between NRR and business performance. However, this may not tell the whole story. Tech companies often struggle to balance product innovation with delivering strong customer experiences. Many also lack the ability to measure key data points, or rely on too few, limiting visibility into their service operations. For example, the treatment of customer lifetime value (CLV) as a mid-level priority may be hindering sustainable growth. Unlike NRR, CLV takes a longer-term view, helping identify high-value customers, guide resource allocation, and inform where to deploy agents, personalization, or automation. The shift toward consumption-based models makes CLV even more critical, as it can identify which customers drive long-term value and which are at risk of churning. # NRR Is Important, but Not Enough Net revenue retention in high performers vs. low performers Customer and account metrics being tracked by tech companies # 4 # The Agentic Era Has Arrived # The Agentic Enterprise Needs Better Data The majority of tech leaders agree that AI – particularly agentic AI – is of value across the entirety of their organization. However, despite AI being a top area of investment – second only to product innovation – only $14 \%$ of tech companies have fully integrated their data, creating a delta between AI investment and actual implementation. Leaders cite disconnected data as one of their top overall challenges – and it’s blocking AI agents from realizing their potential to transform the agentic enterprise. AI agents are key to boosting productivity, reducing costs, and driving the kind of growth tech companies need, but implementation challenges primarily tied to data security and insufficient data quality are holding them back from achieving these goals. Some companies have tried to address these problems through data lakes or warehouses. However, powering high-performing, front office agentic capabilities requires something more. # AI Can Transform Your Business – If Your Data and Teams Are Ready Tech leaders' level of agreement with the following statements Top challenges faced by tech companies when implementing generative or agentic AI 1 Data security and privacy concerns 2 Uncertainty regarding model accuracy 3 Insufficient/poor data quality to support AI 4 Workforce skill gaps/upskilling 5 Lack of understanding of capabilities or use cases 46% of tech companies don’t believe their teams have the data they need to do their jobs. # Agentic AI Gains Steam, but Strategy Lags At present, customer service, lead qualification, and data visualization continue to be the top-cited agentic AI use cases. This indicates that go-to-market functions are viewed as the easiest and most natural place to start implementing these capabilities. But, only $45 \%$ of tech companies have a clearly defined AI strategy, which may explain where companies see value and where they’re actually deploying agents doesn’t always match up. Trust also plays a role, with $48 \%$ of tech leaders trusting AI agents to provide accurate results but only $37 \%$ trusting AI agents to act autonomously. It should be noted that this gap in trust varies across departments and is seemingly narrower in departments such as customer service, where people are already used to the idea (chatbots), than in sales, where sellers are more reluctant to relinquish direct contact with their prospects. # Agentic AI's Biggest Opportunity: Go-to-Market Functions Top-ranked priorities for generative and agentic AI use cases 1 Customer service/troubleshooting 2 Knowledge creation 3 Data visualization 4 Lead qualification 5 Campaign creation Agentic AI usage by role # Spotlight: Build vs. Buy As tech leaders turn to product innovation to fuel growth and elevate customer experience, they're betting that increased AI investments will help. However, many are also spending time and money building agentic AI into their front-office operations. This is understandable, given that $75 \%$ of AI’s value lies in the front office. However, while an investment in agentic AI across go- to- market functions can unlock efficiencies, real growth and ROI come from building AI into your core products – and buying AI to accelerate go- to- market functions. Out-of-the-box front office solutions allow tech companies to benefit from the agentic capabilities they need without incurring the costs in time, money, and increased headcount. These savings can then be put back into R&D and product development to bolster product innovation, and their competitive edge, even more. # Don’t DIY Your Front-Office Agentic AI Agentforce vs. do-it-yourself methods Source: Valoir, Accelerating Time to Agentic AI Value, 2025 # Look Ahead: The Future Belongs to Agentic Enterprises In an environment rife with competition and economic challenges, agility, differentiation, and a solid data and AI operation become critical to cost-effective, efficient growth. The agentic enterprise will be the key to success across all areas. However, proper integration and a clearly defined strategy matter. A huge part of that strategy lies in the decisions made around where and how to invest in these types of solutions. An out-of-the-box data and AI platform is a strategic investment allowing organizations to benefit from the most up-to-date, cutting-edge front office AI solutions without having to get bogged down in operational systems and processes. Success lies in the growth, innovation, and differentiation that comes as a result of delivering superior products and services. Organizations that can achieve this will drive revenue, edge out the competition, and keep customers coming back time and again. # Plan Smarter, Win Bigger with AI Demand for AI products and services is surging 1.3T Projected generative AI market over the next 10 years \$280B New software revenue from rising GenAI demand Source: Bloomberg, Generative AI to Become a $1.3 Trillion Market by 2032. Agentforce accurately resolves $70 \%$ of day- to- day chat inquiries, 24/7 Salesforce, Datasite Customer Story. Datasite # Explore More Technology Resources # AI Agents Tech Industry Guide See how you can fuel the future with data-driven, genetic solutions. # Agentforce for Technology Agentforce helps tech companies grow revenue and retention faster – with digital labor, not more headcount. # Agentforce for Technology Demo Accelerate your journey to becoming an agentic enterprise with Salesforce. Get the guide Learn more Watch demo # Sample Details # Sample Details # Country Australia $N = 12,2.7\%$ Brazil $N = 7,1.6\%$ Canada . $N = 17,3.8\%$ France $N = 15,3.3\%$ Germany $N = 26,5.8\%$ India $N = 37,8.2\%$ Ireland $N = 0,0\%$ Israel $N = 5,1.1\%$ Italy $N = 5,1.1\%$ Japan $N = 7,1.6\%$ Mexico $N = 0, 0\%$ Netherlands $N = 7,1.6\%$ New Zealand $N = 1,0.2\%$ Nordics (Denmark, Finland, Norway, Sweden) $\dots \dots \dots N = 4$ , $0.8\%$ Portugal $N = 2,0.4\%$ Singapore $N = 6,1.3\%$ Spain $N = 8,1.8\%$ Switzerland $N = 0, 0\%$ United Kingdom . $N = 40,8.9\%$ United States .N=238, 52.9% Other $N = 11,2.4\%$ # Department Sales $N = 60,13.3\%$ Customer Service and Support $N = 22,4.9\%$ Marketing . $N = 112, 24.9\%$ Product Management . $N = 99,22\%$ Business Operations .N=46, 10.2% IT/IS .N=111,24.7% # Company Size 1 to 50 employees . $N = 41,9.1 \%$ 51-200 employees $N = 56, 12.4\%$ 201-1,000 employees $N = 69$ , $15.3\%$ 1,001-5,000 employees $N = 79$ , $17.6\%$ 5,001- 10,000 employees. N=68, 15.1% 10,001-25,000 employees $N = 47$ , $10.4\%$ 25,000+ employees .N=90, 20% # Industry Sub-Sector Software and Services N=333, 74% Hardware . $N = 56,12.4\%$ Semiconductor/Contract Manufacturing....N=61, 13.6% # Role Level C-Suite/Owner/Founder $N = 84$ $18.7 \%$ VP/SVP N=130, 28.9% Senior Director/Director N=236, 52.4% # salesforce The information provided in this report is strictly for the convenience of our customers and is for general informational purposes only. Publication by Salesforce does not constitute an endorsement. Salesforce does not warrant the accuracy or completeness of any information, text, graphics, links, or other items contained within this guide. Salesforce does not guarantee you will achieve any specific results if you follow any advice in the report. 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