As we stand on the edge of 2025, I’m reminded of one fundamental truth: disruption waits for no one. Organizations and leaders who can anticipate, adapt, and act quickly will thrive. At The Futurum Group, we are focused on helping you decode the complexities of today’s digital-first world so you can stay ahead of the curve.
This year’s predictions dive deep into the trends reshaping industries—from AI’s pervasive influence across enterprise applications to seismic shifts in hardware, cloud, and customer experience. Our team of analysts—some of the brightest minds in research and strategy has dissected the forces driving change and outlined actionable insights for what’s next.
Whether it’s the rise of agentic AI disrupting software consumption, cloud marketplaces revolutionizing GTM strategies, or the accelerating impact of AI PCs on productivity, the message is clear: we are entering a new era where business agility, intelligence, and innovation are the ultimate differentiators.
The insights shared here are not just about spotting trends but about preparing for
transformation. As customer expectations soar and competition intensifies, companies that embrace change as an opportunity rather than a challenge will set the pace for the next decade.
I invite you to explore the predictions in this report and reflect on how your organization can harness these shifts to drive growth, improve outcomes, and elevate experiences for customers and employees alike.
Here’s to meeting the future head-on—together.
Chief Strategy and Research Officer
By the end of 2025, we will see a significant shift in how enterprise software is consumed. At least 30% of routine business software interactions will be mediated through AI agents rather than direct user interfaces, leading to a fundamental restructuring of software licensing models.
“The rise of agentic AI represents a significant shift in enterprise software. Instead of employees juggling dozens of different applications and interfaces, they’ll simply tell AI agents what they need to do – onboarding a new hire or reconciling financial data across systems – and the agents will handle the complex coordination behind the scenes. This isn’t just about automation; it’s about fundamentally changing how businesses – and the people within them – interact with their software systems, potentially saving billions in training costs and dramatically reducing the cognitive load on workers to free them up for more productive and creative tasks.”
Vice President & Practice Lead
AI Software & Tools
The convergence of three key factors accelerates this trend.
AI-capable PCs (PCs equipped with an NPU and capable of running some AI training and inference workloads locally) will come to represent at least 40% of new PC shipments by the end of 2025.
Research Director & Practice Lead
AI Devices
Three primary reasons are driving this change.
As AI-capable PCs are an evolution of pre-AI PCs, all previous use cases for PCs still apply. However, new use cases have already begun and will continue to emerge.
Cloud marketplaces will become as big a Go-to-Market (GTM) for Independent Software Vendors (ISVs) as traditional distribution is for commercial hardware. Over $300 billion of committed cloud spending will continue to help fuel this engine.
“Every vendor is trying to figure out their marketplace strategy, which ones to prioritize, how to operationalize it, and how to bring traditional partners on that journey. The most successful vendors in the marketplace will be the ones that understand how to include service delivery partners as part of their marketplace strategy.”
Vice President & Practice Lead
Channels & GTM
Enterprise IT will undergo a dramatic transformation in 2025, as CIOs strategically re-architect their cloud infrastructure to meet the demands of AI-driven workloads. According to Futurum’s latest CIO Insights survey, 89% of CIOs report leveraging AI for strategic improvements, with 71% reevaluating the optimal environments for running cloud workloads.
“As AI becomes integral to business strategy, CIOs are being forced to reconsider how and where it’s optimal to deploy compute resources. The need for low latency, cost efficiency, and compliance in AI applications is driving a rapid shift toward hybrid and multi-cloud strategies. For IT leaders, this means 2025 will be a pivotal year for a comprehensive realignment of their infrastructure with the realities of the AI era.”
Vice President & Practice Lead
CIO Insights
Three primary reasons are driving this change.
Generative AI will become an increasingly important differentiator across the cybersecurity toolchain. In fact, more than 40% of cybersecurity decisionmakers noted the integration of new technologies such as generative AI as a top spending priority relating to cybersecurity, and 39% note new AI-driven security platforms, in The Futurum Group’s Cybersecurity Decision Maker IQ data.
“As attackers use AI to elevate their game, organizations must also start evaluating AI as an important tool to fight back. Cybersecurity vendors are responding by steadily integrating generative AI into their solutions for a myriad of outcomes. These include enhancing vulnerability and threat detection and automating routine tasks, in order to reduce the likelihood of a successful attack, and the resulting impact of successful breaches. This approach will only increase in its criticality to helping organizations to protect their most important data assets and optimizing the resilience of their most critical business services.”
Research Director & Practice Lead
Cybersecurity
Three primary reasons are driving this change.
By the end of 2025, generative AI will be valued just as much, if not more, for its ability to reduce developer toil and tackle technical debt compared to its ability to generate new code.
“Generative AI is not only revolutionizing new software development, it is also fundamentally changing how software developers work with existing codebases. Software development relies upon the human ability to understand the interdependencies and inner workings of software codebases, a natural use case for generative AI. Agentic AI will have a profound impact at tackling the mountain of technical debt and reducing the toil developers deal with as part of their everyday work.”
Vice President & Practice Lead
DevOps & Application Development
Three primary reasons are driving this change.
Generative AI-powered features will enter widespread use in 2025, thereby requiring significant shifts in pricing models, with seat-license models being supplanted by consumption-based and outcomes-based approaches. A 2024 Futurum Intelligence survey of 895 decision-makers and influencers found that 40% of respondents were paying for software on a consumption-based pricing model, and 15% were using an outcomes-based model.
“The combination of generative AI and automation technologies has rapidly transformed the ability of vendors to deliver far more functionality within its software offerings, resulting in significant advances in productivity, efficiency, accuracy, and other metrics. However, these advanced features are the direct
result of compute power, which can be expensive for vendors to provide, either because their volume of utilization is low and the unit cost is high or because the volume of customer usage is so high that they’re simply burning through a high volume of compute resources. New pricing models are required to align the economic model for both customers and vendors more closely and fairly while providing additional transparency.”
Research Director & Practice Lead
Enterprise Applications
Three primary reasons are driving this change.
There are several examples of these new pricing models being used today:
Chiplets will account for an increasing share of semiconductor foundry services with some leading advanced packaging equipment suppliers expecting chiplets to account for 25% of foundry revenue by 2030
Source: BESI Ivestor Presentation, November 2024.
“As the monolithic scaling associated with Moore’s Law has become increasingly economically unviable as a driver of semiconductor performance and cost improvements, so the demands of future applications, such as AI processing, have become even more onerous. We will see an increasing share of industry investment (both R&D and CAPEX) directed towards the advanced packaging technology required to deliver heterogeneous integration of chiplets.”
Vice President & Practice Lead
Semiconductors
Industry Economics: For decades, Moore’s Law delivered performance and cost improvements through shrinking transistor geometries, increased die sizes and larger diameter wafers. As overcoming the technical challenges associated with this monolithic scaling has become too expensive to justify for all but a few semiconductor device types, industry investment has shifted more towards advances in packaging technology.
Cost Optimization: By partitioning the chip into separate functional elements (chiplets), only the advanced logic functions need to be fabricated on leading-edge process nodes. Less-critical functions can be processed using legacy nodes or a different process technology altogether. Chiplets also have the advantage of the higher yields typically associated with smaller die.
Performance Benefits: In addition to facilitating higher-speed data processing and transfer, heterogeneous integration also enables lower power consumption and better heat dissipation, which are increasingly important system performance metrics.