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In December 2025, we published our analysis of the global memory shortage crisis and its potential impact on the PC and smartphone markets heading into 2026. At that time, we outlined two negative-impact scenarios, ranging from low single-digit to high single-digit market declines. This week, IDC released updated forecasts for both the worldwide PC and mobile phone markets, and the outlook has become significantly worse. The current situation is now more negative than even our most pessimistic scenarios suggested just a few months ago.

The market pull-forward

As concerns about DRAM and NAND pricing escalated in late 2025, vendors across both the PC and smartphone categories moved aggressively to get ahead of the problem. Shipments ramped significantly in the fourth quarter of 2025, as noted in our recent press releases on Q4 2025 PC historical shipment data and mobile phone historical shipment data. These elevated levels have continued into the first quarter of 2026 for the PC market, as OEMs rush to ship products before memory and storage price increases take full effect. The result is that we now expect Q1 2026, which ends in March, to come in significantly higher than our November forecasts for PCs.  For smartphones, the situation is exasperated, with Q1 2026 forecast to decline 6.8%As memory prices climb and some vendors, particularly smaller ones, struggle to secure and/or pay for adequate supply, we expect unit volumes to fall off dramatically beginning in the second quarter. Average selling prices (ASPs) will rise, but volume demand will weaken in response. The net effect will be negative year-over-year unit growth for the full year, even as the revenue picture looks deceptively stable due to inflated ASPs.

For PCs, we are now forecasting the worldwide market to decline by 11.3% in 2026, while revenues grow 1.6% due to increased ASPs. Our current forecast shows the market flattening in 2027, with a rebound now pushed out to 2028. The smartphone market looks even more dire, as we’re currently forecasting the worldwide market to decline by 12.9% in 2026, with revenues declining slightly by 0.5%. We expect 2027 to see a modest 1.9% growth for smartphones, with a stronger 5.2% rebound in 2028.

IDC expects the memory supply challenges to persist throughout 2026 and likely well into 2027. While we do anticipate that the rate of memory price acceleration will slow in the second half of this year, prices will continue to rise and remain elevated. Based on current assumptions, our model does not point to a reversion to 2025 pricing levels within the forecast horizon.  The structural dynamics driving the shortage, surging AI infrastructure demand competing with consumer device needs for the same DRAM and NAND capacity, remain firmly in place. There may be some relief as memory capacity buildouts increase and smaller memory suppliers in China come into play.  However, we do not expect it to offset the shortage in a meaningful way and change the trajectory of the crisis.

The downstream consequences of the crisis are becoming clearer and will reshape competitive dynamics in the PC and smartphone markets described here, as well as in other device markets such as tablets, XR headsets, wearables, and gaming consoles.

Share shifts favoring larger vendors

Companies with greater purchasing power, stronger supplier relationships, and the ability to commit to large-volume contracts will be better positioned to secure memory allocations at high, but more manageable prices. Smaller and regional vendors, already operating on thinner margins, will find it increasingly difficult to compete for supply. We expect meaningful market share shifts in favor of the largest global OEMs over the course of 2026.

We also expect vendors to begin shipping some new devices with less memory than consumers have grown accustomed to. Rather than absorbing the full cost of higher-priced memory, some OEMs will opt to reduce average DRAM and NAND configurations in their products. A phone that might have shipped with 12GB of RAM and 256GB of storage a year ago may now debut with 8GB of RAM and 128GB of storage at the same price point, or worse. The same dynamic will play out in PCs, where base configurations could see meaningful reductions in RAM and SSD capacity.

The lower end of both markets will bear the brunt of the impact. Budget smartphones and entry-level PCs operate on razor-thin margins, leaving vendors with little room to absorb price increases. The math simply does not work for a $150 smartphone or a $400 laptop when memory costs surge by double and even triple digit percentages quarter over quarter. Many vendors will either exit price points entirely or deliver products with specifications that are noticeably degraded, at likely higher prices. For consumers and small businesses already sensitive to pricing, this will push many to delay planned device purchases, extending replacement cycles and further depressing unit volumes.

For the smartphone market, the implications are especially severe. Last year, more than 360 million smartphones shipped below $150, representing a substantial share of global volumes, with that proportion rising in key emerging markets like Africa and India, to nearly 60% and 30%.  As rising memory costs render this price band economically unsustainable, the industry faces a reversal of a decade long trend in which consumers consistently received smartphones with better specifications at lower prices. Most low‑end–focused OEMs plan to defend share by cutting specifications or shifting volume above $200, but demand in that range remains limited across emerging markets, making it impossible to sustain current shipments. They will also face stronger competition from established brands at higher tiers, further limiting their ability to preserve volume and share.  As a result, we expect a significant reduction of Total Addressable Market (TAM) through the current forecast period and a consolidation of the competitive landscape. Meanwhile, demand for budget smartphones will persist, pushing price‑sensitive consumers to either extend device lifecycles or turn to affordable used smartphones, where adoption is already accelerating.  Consumers in some emerging markets could even revert to feature phones, reversing smartphone penetration gains as ultra-low end smartphones below $50 cease to exist.  In short, the smartphone market is headed for a structural reset, in size, product mix, and competitive landscape.

The memory mix-down trend is particularly concerning for the AI PC category. Despite heavy marketing investment and the integration of dedicated Neural Processing Units (NPUs), AI PCs have so far failed to deliver on the transformative capabilities promised to consumers and enterprise buyers. The use cases remain narrow, and the software ecosystem has not kept pace with the hardware. Now, just as the industry needs to build a more compelling AI story around the PC, the memory crisis threatens to undermine the foundation required to do so. Local AI workloads, including the vision of the PC at the center of an Agentic AI future capable of managing and coordinating multiple AI tasks on behalf of the user, are inherently memory intensive. Shipping systems with less RAM does more than just limit today’s AI capabilities. It constrains the potential of these devices to run local models, manage context windows, and handle the data throughput that meaningful on-device AI will demand.

Tariff uncertainty adds another layer of risk

The policy environment is adding its own volatility. Last week, the U.S. Supreme Court struck down the broad reciprocal tariff regime imposed by the Trump administration, ruling that the executive authority exercised exceeded its statutory scope. The administration has since moved to levy a 10% across-the-board tariff on imports using alternative legal authority, and is working to raise it to 15.

For the device industry, this creates deep uncertainty. A 15% tariff on finished goods and components layers additional cost pressure on top of already-inflated memory prices. Vendors cannot plan pricing, sourcing, or inventory strategies with any confidence. Some costs will be passed through to consumers, compounding affordability challenges. Others will be absorbed by vendors and channel partners, further compressing margins.

Buckle up

The bottom line is that 2026 is shaping up to be another challenging year for the PC and smartphone markets. The confluence of a deepening memory supply crisis, aggressive pull-forward activity that has front-loaded volumes, rising ASPs that will suppress unit growth, and a volatile trade policy landscape makes precision forecasting extraordinarily difficult. Organizations across the value chain, from semiconductor suppliers to device OEMs to channel partners and enterprise buyers, should be planning for sustained turbulence. This is not a one-quarter disruption. It is a structural shift that will define the device market narrative well into 2027.

Nabila Popal - Sr. Director, Data & Analytics - IDC

Analyst Profile
Nabila Popal is Senor Director with IDC's Data & Analytics team, specializing in Mobile Phones, PC Monitors and other consumer devices. Ms. Popal is responsible for the global research and quality and timely delivery for her respective technologies, coordinating with regional and worldwide research teams. She continuously engages with global vendors and key market players to discuss the latest industry trends and dynamics. Ms. Popal is also responsible for future product planning and evolution whilst managing client relationships and providing thought leadership and executing custom engagements. She also manages communications with the media and is often published in leading local and international media outlets. Ms. Popal has been with IDC since 2013, and prior to her role with the Worldwide team, she was with IDC MEA, leading the research for Middle East, Africa, and Turkey, based out of Dubai, UAE.

Ryan Reith - Group Vice President, WW Device Trackers - IDC

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Ryan Reith is the Group Vice President for IDC's Worldwide Device Tracker suite, which includes mobile phones, tablets, wearables, and most recently AR/VR. His teams research focuses on the quantitative aspects of the mobile device industry, including market sizing, forecasting, vendor market share analysis, and technology trends. His current responsibilities include engaging with mobile device OEMs, supply chain, distributors, and the financial industry to discuss market trends and forward looking analysis.

Jeff Janukowicz - Research Vice President, Solid State Drives and Enabling Technologies - IDC

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Jeff Janukowicz is a Research Vice President at IDC where he provides insight and analysis on the SSD market for the Client PC, Enterprise Data Center, and Cloud market segments. In this role, Jeff provides expert opinion, in-depth market research, and strategic analysis on the dynamics, trends, and opportunities facing the industry. His research includes market forecasts, market share reports, and technology trends of clients, investor, suppliers, and manufacturers.

Tom Mainelli - Group Vice President - IDC

Analyst Profile
Tom Mainelli heads the Device & Consumer Research Group, overseeing a wide array of hardware and technology categories that cater to both home and enterprise markets. His team's research spans PCs, tablets, smartphones, wearables, smart home devices, thin clients, displays, and virtual/augmented reality headsets. He also co-manages IDC's supply-side research team, which monitors display and ODM production across various categories. IDC's consumer research, anchored by the Consumer Market Model, employs regular surveys and proprietary models to forecast numerous consumer-focused activities and spending across hardware, software, and services. As Group Vice President, Tom collaborates closely with company representatives, industry contacts, and other IDC analysts to provide comprehensive insights and analysis on a diverse range of commercial and consumer topics. A frequent speaker at public events, he travels extensively, enjoying every opportunity to engage with colleagues and clients worldwide.

Francisco Jeronimo - Vice President, Data & Analytics - Devices - IDC

Analyst Profile
Francisco Jeronimo is VP for Data and Analytics at IDC EMEA. Based in London, he leads the research that covers mobile devices, personal computing devices, emerging technologies and the circular economy trends across EMEA. His team delivers data on personal computers, tablets, smartphones, wearables, PC monitors, PC gaming, enterprise Thin Client devices, smart home, augmented reality and virtual reality, and sales of used devices. He provides in-depth analysis of the strategies and performance of the key industry players.

Bryan Ma - Vice President - IDC

Analyst Profile
Bryan Ma is Vice President of Client Devices research, covering mobile phones, tablets, PCs, AR/VR headsets, wearables, thin clients, and monitors across Asia as well as worldwide. Based in Singapore, Bryan provides insights and advisory services for both vendors and users, and coordinates his team of analysts in building IDC's core market data, analysis, and forecasts in these sectors. Bryan has been quoted in a number of publications, including The Wall Street Journal, The Economist, The Financial Times, BusinessWeek, The South China Morning Post, and The New York Times. He has been a featured speaker at numerous industry conferences and appears frequently as a guest commentator on television networks such as CNBC, Bloomberg, and the BBC.

Recent tariff developments are adding cost pressure and uncertainty across global technology supply chains.

In a recent discussion, IDC’s Simon Ellis, Group Vice President of Manufacturing and Supply Chain, and Phil Solis, Research Director of Connectivity and Smartphone Semiconductors, assess what the latest tariff developments mean for pricing, manufacturing strategy, and long-term investment decisions across the technology ecosystem.

Uncertainty is the immediate business challenge

While the Supreme Court ruled that certain prior tariffs were not legal, new tariffs are now being implemented. As a result, cost exposure remains, and the broader issue for many organizations is unpredictability.

“There just isn’t a lot of clarity around these things. What is true on a Monday is no longer true on a Tuesday. It’s hard to know what the right thing to do is because many of the structural things that companies have to do don’t take minutes or hours or days or even weeks. They can take months or even years.”

Simon Ellis, Group Vice President, IDC

For manufacturers and supply chain leaders, structural decisions such as facility investments, sourcing changes, or regional expansion are made on multi-year horizons. When policy direction shifts quickly, organizations must weigh whether to proceed, delay, or absorb incremental risk.

Pricing discipline in a volatile environment

Tariff exposure is layered on top of other cost pressures, including rising memory prices that affect smartphones, PCs, and servers.

“Assuming that these tariffs are in place for some time to come, they will leave their prices higher to account for that. It’s harder to lower prices and then re-raise them. It’s just too chaotic.”

Phil Solis, Research Director, IDC

Pricing decisions are not made lightly. When structural costs increase, prices typically follow. When costs decline, prices do not always adjust at the same pace. In an environment where additional tariffs may persist, companies are cautious about lowering prices only to reverse course later.

Cross-border complexity and tariff stacking

Modern technology products often cross borders multiple times before reaching the end customer. A semiconductor may be imported, incorporated into a module, integrated into a subsystem, and ultimately assembled into a finished product.

Each stage can introduce additional cost exposure. This stacking effect can compound pricing pressure across the value chain.

For organizations operating complex global supply networks, tracking and tracing components across jurisdictions becomes increasingly important for cost management and compliance.

Balancing efficiency and resilience

Since the pandemic, companies have navigated a persistent tension between supply chain efficiency and resilience. Tariffs represent another disruption that must be incorporated into that balance.

Increasing resilience through multi-sourcing or excess capacity can reduce risk. However, those strategies carry additional cost. Technology leaders must determine where flexibility is essential and where efficiency remains the priority.

Navigating the next move

Major manufacturing and infrastructure decisions are often made with ten- or twenty-year horizons. In a short-term policy environment marked by volatility, long-term planning becomes more complex.

For technology vendors, manufacturers, and enterprise buyers alike, the central challenge is maintaining disciplined decision-making amid continued uncertainty.

Watch the full conversation above for IDC’s detailed perspective on how these developments may shape the technology market in the months ahead.

In the early 2020s, most IT dashboards looked deliciously green – until you cut them open. That “watermelon problem” summed up the gap between what SLAs said and how people actually felt at work: 99.8% uptime on paper, but slow logons, clunky multi-factor authentication, and chatbots that couldn’t understand what anyone really wanted. Experience was an afterthought, AI was a sideshow, and creativity was nowhere to be found in the contract.​

When SLAs ruled the world

Back then, three things defined the status quo. AI was narrow and local, sitting on the edge of workflows answering FAQs or routing tickets rather than orchestrating work. Experience measurement lagged reality, with annual or quarterly surveys surfacing issues long after the damage was done. And creativity simply didn’t exist in the metrics; contracts cared about uptime, not whether people had the cognitive space to experiment or innovate.​

The result was a strange split-screen. On one side, leaders proudly cited their SLA success. On the other, employees wrestled with friction that didn’t fit any KPI: context-switching between tools, re-entering the same data, and watching “helpful” chatbots miss the point. XLAs were occasionally piloted  (an NPS here, a satisfaction score there) but rarely changed actual design or investment decisions.​

Now: XLAs as control towers for human-AI work

Fast forward to 2026, and AI is no longer the sidekick; it is the backbone of digital work. GenAI assistants, low-code agents, and orchestration platforms now sit inside service desks, digital workplace platforms, and line-of-business apps. XLAs have emerged as the language that decides whether all this AI is genuinely helping humans do better work or just adding more noise.​

Three big shifts define the “now.” Agentic AI makes XLAs real-time and contextual, correlating technical signals like latency and crashes with human signals such as sentiment, task completion, and time to productivity. It can trigger automated remediation, from self-healing endpoints to conversational agents that guide users through fixes, and spotlight experience hotspots for specific personas or workflows. IDC’s 2025 Future of Work survey shows 79% of organizations now actively measure the relationship between employee and customer experience, with two-thirds having proof of causal linkages, while 94% of AI-enabled work adopters report productivity gains and over half see significant improvements.​

Making creativity a measurable outcome

The most interesting XLAs no longer treat creativity as a fuzzy aspiration. They track uninterrupted focus time per persona, link AI automation to freed-up hours, and measure innovation throughput:  ideas submitted, prototypes built, experiments completed. Instead of only asking if AI is fast or accurate, organizations track “human-plus” metrics: how much better decisions, proposals, and options become when humans and AI work together.​

Governance grows up

This evolution is forcing governance structures to grow up fast. AI-focused Centers of Excellence increasingly use XLA dashboards as strategic instruments, challenging deployments that look great on technical metrics but poor on human outcomes. They prioritize changes that build trust and agency, such as better explainability, robust feedback loops, and human override capabilities, and retire tools that consistently score badly on ease of use or learning curve.​

Metrics are diversifying accordingly: about 69% of organizations use productivity scores such as task-based speed and throughput to assess AI, while 42% also track employee satisfaction and 44% monitor skills proficiency. XLAs have become a proxy for hard questions: Are we making it easier for people to solve novel problems? Are AI tools empowering experts or boxing them in? Where is digital friction quietly killing initiative?​

Tomorrow: XLAs as the OS for co-creation

Looking ahead, XLAs are set to become the operating system for human/AI co-creation. Emerging “experience-risk” indices predict burnout or disengagement, while creativity capacity scores combine focus time, use of exploratory tools, and psychological safety indicators. Agentic AI will increasingly use XLAs as experience-intent parameters  – goals like maximizing focus time for data scientists or ensuring frontline staff resolve most issues in under three minutes  – and autonomously orchestrate tools, notifications, and workflows to hit them.​

Contracts will catch up too, moving from green dashboards to models that reward innovation, protect against “experience debt,” and explicitly safeguard time and cognitive bandwidth for meaningful work. For service providers, the mandate is clear: anchor XLAs on outcomes only humans can deliver, make creativity visible on the dashboard, build strong feedback loops, and use XLAs as guardrails against over-automation. XLAs are no longer just a friendlier way to measure IT; they are becoming the central platform for keeping human potential at the center of an AI-driven future of work.

For more information see IDCs upcoming research documents: “Measuring What Matters: XLAs and the 2026 Digital Workplace” and “Control Towers for Human Potential: The Growing Importance of XLAs in the Age of Agentic AI”.

If you have a question about this or any other IDC research, drop it in here.

Meike Escherich - Associate Research Director, European Future of Work - IDC

Analyst Profile
Meike Escherich is an associate research director with IDC's European Future of Work practice, based in the UK. In this role, she provides coverage of key technology trends across the Future of Work, specializing in how to enable and foster teamwork in a flexible work environment. Her research looks at how technologies influence workers' skills and behaviors, organizational culture, worker experience and how the workspace itself is enabling the future enterprise.

Worldwide tablet shipments grew 1.9% year over year in 4Q25, reaching 40.9 million units, according to IDC’s Worldwide Quarterly Personal Computing Device Tracker.

For full-year 2025, shipments increased 5% year over year to 151.9 million units, reflecting sustained replacement demand earlier in the year, strategic portfolio refreshes, subsidy-driven sales in the PRC, and education-led deployments across regions.

While replacement-driven growth tapered in the second half, seasonal promotions, particularly from premium vendors, helped stabilize the market heading into 2026.

What drove tablet market growth in 4Q25?

Several factors supported growth in the quarter:

1. Seasonal promotions from premium vendors

Holiday discounting—particularly across Apple’s portfolio—stimulated volume during peak promotional periods.

2. Education and government projects

Institutional deployments provided pockets of resilience, especially in APJ and Europe, partially offsetting softer retail momentum.

3. Shipment pull-forward ahead of 2026 memory constraints

Vendors and channel partners accelerated shipments in anticipation of expected memory supply tightness and pricing pressure in 2026.

The result: modest but meaningful year-over-year expansion despite a more cautious consumer environment.

Vendor performance: Market share and momentum

Apple maintains leadership

Apple shipped 17.1 million units in 4Q25, capturing 41.9% market share and delivering 8% year-over-year growth.

Entry-level iPads accounted for nearly 52% of Apple’s quarterly sales, with additional support from iPad Air 2024 and refreshed iPad Pro models.

Samsung faces share pressure

Samsung retained the #2 position with 6.4 million shipments but declined 7.5% year over year, reflecting competitive promotional intensity.

Lenovo expands in EMEA and PRC

Lenovo delivered 35.3% year-over-year growth, shipping 3.9 million units and benefiting from XiaoxinPad and Y700 performance in the PRC.

Xiaomi and Huawei navigate PRC subsidy tightening

Both vendors experienced subsidy-related softness domestically but offset pressure with regional expansion. Xiaomi grew 15.8% year over year, while Huawei rose 4.9%.

Full-year 2025 outlook: Replacement wave normalizes

The tablet market began 2025 supported by a post-pandemic replacement cycle. As the year progressed, that demand moderated, resulting in more measured growth in the second half.

According to IDC:

The 2025 tablet market began the year supported by a wave of replacement demand… However, as the year progressed, replacement-driven demand gradually tapered, leading to more measured growth in the second half of 2025.

With 151.9 million units shipped in 2025, the market closed the year on more normalized footing.

What this means for 2026

As the industry moves into 2026, three dynamics will shape performance:

  • Anticipated memory supply constraints
  • Inventory planning adjustments
  • Heightened competitive pricing strategies

Vendors that balance innovation, cost discipline, and promotional execution will be best positioned to defend share in a more stabilized demand environment.

Why this matters for technology suppliers and buyers

For suppliers, the data reinforces the importance of:

  • Portfolio refresh timing
  • Channel strategy discipline
  • Regional demand diversification

For buyers, the moderation of replacement demand suggests:

  • Longer lifecycle planning
  • Increased pricing sensitivity
  • Strategic timing of procurement cycles

IDC’s market intelligence helps both sides navigate these shifts with confidence.

Anuroopa Nataraj - Research Analyst, Worldwide Tablet Tracker - IDC

Analyst Profile LinkedIn
Anuroopa Nataraj is a Research Analyst for IDC's Worldwide Tablet Tracker. Her team's research focuses on the quantitative aspects of the Tablet industry, including market sizing, forecasting, vendor market share analysis, and technology trends.

Growth creates momentum, but it also introduces pressure. 

For technology vendors scaling quickly, the decision to enter new markets or move upmarket often arrives earlier than expected. Boards want evidence of expansion. Investors look for signals of long-term opportunity. Leadership teams feel the urgency to act. In that environment, go-to-market decisions carry more weight and less margin for error. 

IDC analyst Roger Beharry Lall sees this moment frequently. In one recent engagement, a high-growth marketing technology company faced a familiar challenge: how to expand from an SMB-focused business into the enterprise market without losing the foundation that made its growth possible. 

The challenge of moving upmarket 

The organization understood that change was necessary. Growth expectations made that clear. The open question was how to evolve its go-to-market approach in a way that translated existing strengths into enterprise relevance. 

This was not a matter of rebuilding the product or abandoning its core market. It was about understanding how current capabilities should be positioned differently, which buyers actually mattered in the enterprise segment, and where the company’s value would resonate most. 

That kind of clarity is difficult to achieve internally, especially when teams are moving quickly and interpreting market signals in different ways. 

Why this moment mattered

For fast-growing vendors, go-to-market shifts are not abstract strategy exercises. They are closely tied to credibility, momentum, and long-term growth narratives. 

Leadership teams are often under pressure to demonstrate progress into new markets through launches, positioning changes, or expanded offerings. That pressure can compress decision timelines and increase the risk of moving forward without a shared understanding of where demand actually exists. 

IDC frequently works with organizations at this stage. Expansion into enterprise or adjacent segments is common, but success depends on identifying the right subsegments, personas, and verticals rather than treating the market as a single opportunity. 

The risk of getting a go-to-market pivot wrong

The most significant risk in a go-to-market pivot is not missing the new opportunity. It is weakening the business that already works. 

Organizations can lose focus on their anchor revenue if new positioning creates confusion or dilutes the value customers already recognize. Growth initiatives that are not grounded in market reality can introduce friction rather than acceleration.

In this engagement, a critical priority was ensuring that enterprise positioning did not undermine existing strengths. The work focused on translating what the company already did well into a new context, rather than redefining the business altogether. 

This balance is often where go-to-market strategies struggle, particularly under time pressure. 

When internal alignment slows progress 

In high-risk go-to-market pivots like this, internal alignment becomes just as important as identifying the right market opportunity. 

Although the decision to move upmarket had been made and early traction existed, progress stalled for a different reason. 

Teams across marketing, product, executive leadership, and the board did not share a consistent understanding of what the enterprise market required. Assumptions varied, priorities differed, and discussions lacked a common reference point.

This situation is common. Without an external source of validation, internal conversations can circle without resolution. The issue is not disagreement about goals, but uncertainty about how to move forward with confidence. 

Shifting from assumptions to validation 

The engagement with IDC evolved as the organization’s needs became clearer. Rather than relying on a predefined approach, the work focused on bringing together existing research, market data, and analyst interpretation. 

What mattered most was not the volume of information, but the ability to contextualize it. Insights drawn from extensive end-user conversations helped clarify what enterprise readiness actually required, where expectations differed from assumptions, and which paths introduced unnecessary risk. 

This shift allowed the organization to move from analysis into decision-making. 

How the organization engaged with insight 

What mattered next was not just the insight itself, but how the organization chose to work with it. 

One of the strongest indicators of progress was how the organization engaged with the insights themselves. 

The teams did not accept findings at face value. They challenged conclusions, asked questions, and worked through implications together. That interaction helped turn data into understanding and understanding into action.

As a result, insights became inputs for leadership discussions rather than static outputs. 

What changed in how decisions were made 

As shared understanding improved, decision-making became more efficient. 

The organization was able to align internally on priorities, refine target segments, adjust messaging, and focus roadmap discussions. Board-level conversations shifted from whether to move forward to how best to do so. 

Confidence came from alignment, not from certainty about outcomes. 

Early signals that mattered 

While it was still early to measure full market impact, initial signals showed that the strategy was taking hold. 

Messaging and positioning were reworked. Channels were reprioritized. Roadmap considerations, particularly around compliance, became more central to planning and communication. These were meaningful changes that reflected a deeper understanding of enterprise buying dynamics. 

They also indicated that the strategy was being operationalized, not just discussed. 

A takeaway for leaders rethinking go-to-market strategy 

For leaders facing similar decisions, the lesson is clear. 

Speed alone does not create momentum. Alignment does. Independent validation helps organizations move forward with shared understanding, reduce internal friction, and make decisions that hold up under pressure. 

When growth depends on getting go-to-market right, assumptions are rarely sufficient. Market truth provides the foundation for confident execution. 

Speak with an IDC market expert to validate your GTM strategy and align your expansion plans with real enterprise demand.

Businesses are locked in an AI arms race.

Cybercriminals are using generative AI, synthetic identities, and deepfake technology to accelerate attacks. At the same time, security teams are racing to automate detection, streamline response, and embed AI into their defensive posture.

In a recent interview with BizTech Magazine, IDC’s Dr. Grace Trinidad explored what this new reality means for enterprises and why AI-driven cybersecurity is no longer optional.

The bigger story? IDC’s FutureScape 2026 predictions anticipated this structural shift.

What are Synthetic Identity Cyberattacks, and Why are They Scaling?

Synthetic identity phishing uses AI-generated content combined with real personal data to fabricate highly convincing digital identities.

IDC predicts:

By 2027, 80% of organizations will experience phishing attacks from criminals using synthetic identities, mixing real info and AI-generated data to create fabricated identities that appear legitimate.

(IDC FutureScape 2026, Prediction 5, Security and Trust)

This is not a fringe scenario. It represents a structural change in the threat landscape.

Grace highlights a high-profile example in which AI-generated executive replicas convinced an employee to authorize a $25 million transfer. As she notes to BizTech about the firm’s approach:

“Everyone needs a safe word now so that we can verify transactions and make sure that they’re not actually initiated by a fraudulent actor posing as one of our executive staff.”

AI has lowered the barrier to impersonation. Trust frameworks must evolve just as quickly.

Why is High-Quality Telemetry Critical for AI-Driven Cybersecurity?

AI-powered security systems are only as strong as the data that feeds them.

Grace explains to BizTech:

“When you have very high-quality telemetry, that naturally cascades into good AI output.”

This aligns directly with IDC’s broader guidance:

By 2027, companies that do not prioritize high-quality, AI-ready data will struggle scaling GenAI and agentic solutions, resulting in a 15% productivity loss.

(IDC FutureScape 2026, Prediction 6, Worldwide AI and Automation)

In cybersecurity, poor data quality does not just reduce productivity. It increases exposure, slows detection, and amplifies risk.

Telemetry is now the foundation of scalable AI defense.

How Will Breach Response Shift from Static Playbooks to Agentic Orchestration?

Traditional breach response playbooks are static, manually updated, and often disconnected from real-time system conditions.

That model will not survive in an agentic era.

In the article, Grace describes the shift ahead:

“In the next three years, we’re going to see personalized playbooks based on telemetry from that organization’s existing environment captured on the fly, in real time.”

IDC forecasts:

By 2030, 45% of organizations will centrally manage the orchestration of AI Agents to boost employee collaboration, seamlessly scale operations and ensure ethical governance of AI deployments.

(IDC FutureScape 2026, Prediction 9, Worldwide AI-Fueled Business Strategies)

Security will be one of the first domains where orchestration becomes mission critical. Dynamic response. Real-time adaptation. AI agents collaborating with human analysts.

Why is AI Governance the Line Between Innovation and Liability?

AI integration across the enterprise remains uneven. Many organizations are experimenting. Few are fully aligned.

Grace observes in the article:

“We’re not quite there yet… I don’t know any organization that I would say they’re a standout example of AI integrated throughout the enterprise.”

Without governance, AI becomes a new attack surface.

IDC predicts:

By 2028, 100% of Global 100 and 50% of Global 1000 will spend at least $2 million a year on unified AI governance software that includes security, ethics, and privacy as a requirement for innovation.

(IDC FutureScape 2026, Prediction 5, Worldwide AI and Automation)

Governance is not a brake on AI innovation. It is the enabler of safe scale.

What Should CISOs and CIOs Do Now?

To navigate AI-powered cyber risk, leaders should:

  • Audit AI-ready data foundations and telemetry quality.
  • Evaluate controls for synthetic identity detection and identity verification.
  • Modernize breach playbooks toward real-time, adaptive orchestration.
  • Invest in unified AI governance frameworks that integrate security, ethics, and compliance.
  • Establish performance metrics that measure human-AI collaboration, not just automation efficiency.

The AI Arms Race is Structural

Who benefits more from AI, defenders or attackers?

Grace tells BizTech that it a zero-sum game:

“As the ways that we protect ourselves become more dynamic and more responsive and more agile, threat actors are also going to up their game.”

The difference will not be who adopts AI first. It will be who integrates it strategically across data, workforce, governance, and orchestration. Organizations face powerful crosscurrents: geopolitical uncertainty, regulatory shifts, workforce disruption, and now AI-accelerated cyber risk. You cannot control the crosscurrents, but with deliberate strategy, AI-ready data, and agentic orchestration, you can turn turbulence into advantage.

Explore More

To understand how agentic AI will reshape cybersecurity, governance, and enterprise operations in the next 1–5 years, explore IDC FutureScape 2026 predictions and insights.

Read Grace Trinidad’s full interview in BizTech Magazine to hear how these shifts are unfolding now.

Read the BizTech Magazine Article with Grace Trinidad

Ryan Smith - Content Marketing Director - IDC

Ryan Smith is the Director of Content Marketing at IDC, where he leads brand-level content and social media strategy, aligning research insights with compelling storytelling to engage technology decision-makers. With a background in both IT and marketing, Ryan brings a unique blend of technical understanding and creative strategy to his work. He’s also a seasoned storyteller, speaker, and podcast host who believes the right message, told the right way, can drive both trust and transformation.

As AI-powered research becomes a standard tool for business users, speed is no longer the primary challenge. Trust is.

Decision-makers need access to validated research they can rely on, without having to second-guess the quality or credibility of the insights they receive.

That’s why IDC is working with Amazon Web Services (AWS) to bring analyst-validated intelligence directly into Amazon Quick Research, giving business users access to trusted answers in minutes. Quick Research is one of the key capabilities within Amazon Quick, which helps users research topics, gain business insights, and automate workflows.

“AI can dramatically accelerate access to information, but trust, context, and judgment still come from human expertise,” said Eduardo Tobias, Senior Vice President of Product and Strategy at IDC.

The role of analyst-validated intelligence in AI research

Analyst-validated intelligence brings independent judgment and market context into AI-powered research, helping organizations move from information to decisions.

“A lot of us do internet research as part of our jobs, and a lot of information out there is outdated, inaccurate, or misleading,” said Jon Einkauf, Principal Product Manager at AWS and Product Lead for Quick Research. “Sometimes it’s hard for business users to quickly tell what information is reliable and what’s not.”

IDC intelligence addresses that uncertainty by combining proprietary data with global analyst expertise.

“IDC has over 1,000 analysts, global coverage, and decades of credibility with leading companies in the technology space and other verticals,” Einkauf said. “When we were thinking about who we wanted to partner with on Quick Research, it was really important to us that we partnered with a small number of companies that brought very high-quality, very deep insights.”

For AWS, IDC was not simply another data source. It was intelligence that decision-makers already relied on.

IDC’s impact on research outcomes

IDC intelligence is designed to support action, not just analysis. It provides context, perspective, and clear implications that help leaders move forward.

“Whereas the public internet can be fragmented, outdated, or inaccurate, IDC research as a general rule tends to be up to date, very thorough, and very detailed,” Einkauf said.

That distinction matters when research is used to inform real business decisions.

“That kind of insight is really helpful for decision-makers who are using Quick Research and Quick,” he added. “They’re not just looking for insights. They’re also looking to take action.”

Bringing IDC intelligence into Amazon Quick Research

AWS saw the same trust challenge facing business users. Quick Research was built to address it at scale by using agentic AI to help business users plan research, gather information, synthesize findings, and validate citations automatically.

“We oftentimes just don’t have enough time to do the research that we want to do to make the kind of informed decisions that we want to make,” Einkauf said.

Quick Research reduces that burden without sacrificing rigor.

“What we’re trying to do is make it easy for business users to do this kind of complex research and complex analysis and be able to do it in a fraction of the time that it might otherwise take,” he added.

What this collaboration means for organizations

Looking ahead, IDC and AWS see AI-powered research becoming more deeply embedded in everyday enterprise workflows.

“The combination of agentic AI in Quick and this very high-quality, reliable insights from IDC is a really powerful combination,” Einkauf said.

By partnering with AWS, IDC is reinforcing the role of analyst-validated intelligence in the next phase of AI adoption. As organizations rely more on AI-powered research, confidence in the intelligence behind those insights will remain essential.

For organizations navigating complex technology decisions, the takeaway is clear: AI can accelerate research, but trusted intelligence enables confident action.

Learn more about how IDC’s trusted technology intelligence is integrated into Amazon Quick Research to deliver expert-level insights in minutes.

By Bo Lykkegaard, Associate VP for Software Research Europe with advice and review by Ewa Zborowska, Research Director, AI, Europe

Providers of SaaS solutions across the world have been through the market capitalization bloodbath during the past six months. Despite presenting solid indicators of growth and margins for 2025, almost all publicly traded companies have seen share price reductions 10% to 60% with the average reduction being in the 30-35% range.

Forget about looming trade wars, recession fears, missed revenue goals, and other conventional share price depressants. This is about AI disruption of the current SaaS user experience, licensing model, and product architecture. Investors are starting to fear that the SaaS ‘rental model for software’ will become invisible ‘featureware’ inside an AI agent layer.

What Are the Market Cap Reductions Telling Us?

We have examined the market cap reductions of public traded SaaS vendors over the past six months. Based upon this, we can make the following observations:

  • All SaaS vendors are affected across solution areas, geographies, size of vendor, recent growth KPIs, and size focus (SMB vs. enterprise). This means that investors are reexamining their assumptions related to SaaS growth prospects in general.
  • Vendors of workflow automation solutions and vendors targeting small and medium-sized businesses appear particularly exposed. Commercial workflow software is seen as exposed to replacement by new AI agent technologies. Also, vendors targeting small businesses are seen as more exposed to churn and price pressures.
  • SaaS vendors headquartered in EMEA do not appear harder hit than those headquartered in North America and the market cap correction has hit the largest as well as the smaller SaaS vendors.

Changes that All SaaS Vendors Are Facing

Firstly, the conventional SaaS user experience must change. In a conventional SaaS application, the user executes tasks manually within defined workflows. In an AI-powered application, the system adds to these structured workflows with probabilistic outputs, where it generates, predicts, recommends, or executes. Also, AI-powered applications can accept and react to all kinds of conversational user inputs. Furthermore, just like today’s LLM-based apps, business applications understand context and remember past interactions, which make recommendations and predictions more relevant and precise. Finally, AI-powered business applications are more proactive in nature and help users with monitoring tasks and relevant notifications.

Secondly, the conventional SaaS licensing model must evolve. The talk of the town these days is ‘outcome-based pricing’, i.e. the notion of pricing an application on outcomes (e.g. number of invoices issued) as opposed to number of users. If agentic workflows increasingly automate core business processes in the future, the user of a, say, financial application will be an agentic workflow as opposed to a human user. As AI agents increasingly become users of business applications, the user-based revenue model of SaaS application collapses. Investors are looking for SaaS vendors to at least align licensing better to business outcomes.

Thirdly, the conversional SaaS product architecture must be rethought. Adding AI to a conventional SaaS solution in the form of a chatbot or other form of AI-generated add-on does not make a meaningful difference. Real modernization requires rethinking the SaaS workflow from the ground up. AI changes all levels of the SaaS product stack and needs foundation model(s), embedding layer, vector database, retrieval-augmented generation (RAG), orchestration layer, guardrails, monitoring, and prompt/version management.

AI is making several other significant changes in SaaS. Development and maintenance as well as running costs have become more volatile and unpredictable. Data management requires new approaches, as application data now serves as a key source for training AI-powered SaaS solutions. Product roadmaps and release cadences are increasingly driven by AI model upgrades rather than traditional update schedules. Software vendors face new risk management challenges related to hallucinations and regulatory compliance. And both vendors and end-user organizations need to adapt their teams with new sets of skills. And most importantly, the overall competitive landscape has shifted, with AI-based startups and hyperscaler offerings emerging as new challengers.

The changes above certainly apply to SaaS vendors in Europe. However, in addition, vendors in Europe – as they adapt solutions and business models to become AI-driven – must pay particular attention to four areas in order to successfully transform.

Firstly, there is the GDPR, NIS2 and EU AI Act compliance, often accompanied by various national or industry-specific regulations. If they cannot document and showcase complete compliance to customers, they cannot sell their AI-powered solutions to compliance-sensitive European organizations.

Secondly, increasingly we see data residency requirements from customers in Europe, particularly in public services, financial services, and healthcare. Buyers in such industries can require EU-hosted data and sovereign cloud guarantees and approaches and can seek to avoid subjection to the US CLOUD Act and to exposing data for foundation model training.

Thirdly, Europe is multi-lingual and buyers require multi-language model performance. A conversational SaaS application is great but only if the conversation happens in the local European language where the application is deployed. We have seen many cases where non-English conversational capabilities are years behind English.

Fourth, European AI-powered SaaS vendors should expect higher demand for transparency and explainability. European customers have a strong preference for understanding how AI systems make decisions, a need often reinforced by regulations like GDPR and the EU AI Act. This means vendors must provide clear logic behind decision criteria, bias mitigation documentation, human oversight mechanisms, and comprehensive audit trails. Black box AI approaches such as “Pick this candidate because the recruiting application assigned a high AI score” simply will not fly in Europe, where trust is key and it heavily depends on being able to trace and justify how conclusions are reached.

Join the Conversation

At IDC, we help you navigate these changes with deep market research, robust data analytics, and tailored custom solutions. Whether you need strategic insights, benchmarking, or support in adapting your business model, our experts are ready to guide you.

Contact us to discuss your unique challenges and discover how IDC can empower your next steps in the evolving, AI-disrupted European software landscape.

Sources:

Bo Lykkegaard - Associate VP for Software Research Europe - IDC

Analyst Profile
Bo Lykkegaard is associate vice president for the enterprise-software-related expertise centers in Europe. His team focuses on the $172 billion European software market, specifically on business applications, customer experience, business analytics, and artificial intelligence. Specific research areas include market analysis, competitive analysis, end-user case studies and surveys, thought leadership, and custom market models.

When technology leaders are under pressure to prove ROI, credibility matters as much as the numbers themselves. 

IDC’s Business Value practice is designed for organizations that need defensible, customer-backed proof of value, not theoretical models, not marketing claims, and not opinions detached from real outcomes. 

The answers to the most common questions we hear from executives, product leaders, and marketers who are evaluating a Business Value engagement with IDC are: 

What exactly is an IDC Business Value study? 

An IDC Business Value study is a primary-research-based analysis that quantifies the measurable business impact of a technology or solution based on real customer experiences. 

IDC Business Value assets are based on: 

  • In-depth interviews with actual customers 
  • A bespoke and detailed Business Value model based on IDC’s credible Business Value methodology 
  • IDC SME analyst insights 

How does IDC actually calculate ROI and business impact? 

IDC uses a structured, multi-step methodology refined over decades of research. 

At a high level, the process includes: 

  1. Customer interviews to capture pre- and post-deployment conditions 
  2. Quantification of benefits across all benefits associated with the solution, including but not limited to cost reduction, productivity/efficiency gains, security, compliance and risk mitigation, revenue impact, etc. 
  3. Normalization and modeling using IDC proven methodology and standardized assumptions 

      The model is grounded in what customers actually experienced. 

      Who is involved on the IDC side? 

      Business Value projects are led by a dedicated IDC Business Value analyst, supported by: 

      • Project management to keep execution on track 
      • Subject-matter analysts when required 

      Analyst involvement is central, from interviews through final delivery. 

      What is required from you as the client? 

      IDC minimizes client burden while protecting research quality. 

      Typically, clients are asked to: 

      • Participate in an initial kick-off meeting followed by a briefing to align on scope and value drivers 
      • Provide access to a limited set of customer interview candidates (IDC can also recruit) 
      • Review a draft interview guide and assets at defined checkpoints 

      IDC manages IDC recruitment, scheduling and completing interviews, modeling, presentation of results to internal stakeholders and asset creation. The process is collaborative, but tightly run. 

      How long does a Business Value study take? 

      A standard Business Value engagement typically runs ~6 months, depending on: 

      • Speed of interview guide development and customer recruitment 
      • Availability of interviewees 
      • Review turnaround times 

      IDC shares a clear timeline upfront and provides ongoing status updates to keep momentum high and expectations aligned. 

      What external deliverables do clients actually get? 

      Most Business Value engagements include: 

      • A Business Value White Paper (externally usable) 
      • A Business Value Snapshot (a one-page summary of key business value results) 
      • A stand-alone Business Value executive summary (a one-page summary of the key Business Value results) 
      • All assets are IDC-branded, research-backed, and designed to support late-stage buying conversations, not just awareness. 

      Can the results be used in sales and marketing? 

      Yes, and that’s often the primary reason clients invest. 

      Business Value assets are used to: 

      • Reinforce late-stage marketing and sales enablement (e.g., demand gen nurture, ABM programs, sales-facing emails, and social distribution) 
      • Equip sales teams with credible ROI and additional KPI proof points 
      • Provide a credible 3rd party perspective that validates marketing and sales messaging 
      • Accelerate late-stage deals where trust is the blocker 

      Many clients continue using Business Value assets for multiple years across campaigns and regions. 

      What types of companies benefit most from a Business Value study? 

      Business Value studies are best suited for organizations that: 

      • Have Pproducts/solutions still in the adoption cycle where customers need to be convinced of the value 
      • Face buyer skepticism or competitive noise 
      • Need financial proof of value beyond feature claims 
      • Have customers who ask, “Can you prove this?” 

      What happens after the study is complete? 

      IDC doesn’t disappear once the report is delivered. 

      Many clients extend value by: 

      • Leveraging IDC analysts as speakers in sales enablement sessions, executive briefings, and external webcasts 
      • Integrating findings into demand gen and ABM programs, through Business Value tools 
      • Activating Business Value insights across regions or personas 
      • Using IDC to translate and localize insights for regional markets and global audiences 
      • Licensing content and insights for partners, enabling consistent messaging across ecosystems 

      The goal is not just research, it’s impact. 

      Why this matters now 

      As AI, automation, and platform investments accelerate, buyers are under pressure to justify decisions more rigorously than ever. 

      IDC Business Value helps organizations move from claims to confidence, with evidence buyers recognize, trust, and act on. 

      For more: 

      1. Move beyond claims and into evidence buyers recognize as relevant to their situation. Explore how IDC Business Value helps turn relevance into momentum. 
      2. Reach out to a market expert at IDC to explore analyst-led validation solutions, market data and b2b buyer research. 

        IDC - -

        LinkedIn
        International Data Corporation (IDC) is the premier global market intelligence, data, and events provider for the information technology, telecommunications, and consumer technology markets. With more than 1,300 analysts worldwide, IDC offers global, regional, and local expertise on technology and industry opportunities and trends in over 110 countries. IDC’s analysis and insight help IT professionals, business executives, and the investment community make fact-based technology decisions and achieve their key business objectives.

        AI-mediated discovery is changing how buyers find information, form opinions and build trust. For marketing leaders, this shift raises new questions about visibility, credibility and influence long before engagement begins.

        For a long time, digital discovery felt predictable. Search engines, keywords, SEO and funnels shaped how buyers found information. If content was optimised well enough and distributed widely enough, it would eventually be discovered. That assumption no longer holds. 

        In an AI-first economy, discovery is increasingly mediated by intelligent systems that interpret intent, assemble knowledge and prioritise answers across fragmented sources. This shift is subtle but profound. It changes not only how buyers find information, but also when relevance is established and where influence is formed. By the time buyers engage directly, their understanding of the problem space, the category and the credible players is often already shaped. 

        IDC research shows that discovery is evolving from a tactical marketing activity into a strategic capability. Visibility, credibility and authority are formed earlier, indirectly and through systems that organisations do not own or control. 

        From finding information to making sense of it 

        Traditional discovery models are reactive. They respond to explicit queries and rely on static indexing and keyword logic. In practice, they answer what users ask, not why they are asking. 

        Agentic AI introduces a different logic. Instead of retrieving information once, these systems reason about intent, refine discovery paths, validate relevance and adapt outcomes over time. Discovery becomes a continuous sense-making process rather than a single interaction. This distinction matters because most discovery is not transactional. Buyers are trying to understand problems, compare approaches and frame internal conversations long before any commercial intent becomes visible. By the time evaluation begins, discovery has already shaped expectations, trust and default assumptions. 

        In this context, relevance is no longer defined by ranking alone. What matters is whether perspectives, knowledge and data can be interpreted by AI systems as credible, useful and meaningful in answering real buyer questions. 

        Why discovery has become a brand issue

        As AI systems increasingly summarise, synthesise and prioritise information, they also shape perception. Every generated answer reflects a series of decisions about which sources are trusted, which viewpoints are included and which providers are referenced or excluded. Over time, these decisions influence how markets understand categories, solutions and leadership. Discovery therefore becomes the new front line of authority. Even when buyers are not ready to engage commercially, early informational moments shape narratives and build trust long before demand materialises. Organisations that fail to appear in these moments risk becoming invisible, regardless of innovation or execution quality. 

        At the same time, many discussions about discovery still rely on outdated assumptions. Discovery is often equated with visibility, SEO or personalisation. In reality, these are outcomes, not the system itself. Agentic discovery does not replace human judgement, nor does it automate buying decisions end to end. It reshapes how relevance is constructed, combining machine reasoning with human context in a continuous feedback loop that begins well before any buying process formally starts. This shift challenges go-to-market models that assume discovery can be compressed into campaigns, launches or early funnel stages. 

        The European dimension: trust and responsibility

        In Europe, discovery carries additional weight. Trust, transparency and data privacy are not only regulatory requirements, but strategic differentiators. As agentic AI matures, organisations that embed governance, GDPR compliance and transparency into how their knowledge is structured and surfaced are better positioned to build long-term credibility. 

        In this environment, relevance is shaped not only by technological capability, but also by responsibility. Discovery becomes both a performance challenge and a trust challenge. 

        What this means for marketing leaders

        Marketing is not becoming obsolete. It is being redefined.

        In an AI-first economy, discovery rewards organisations that invest in structured, machine-readable knowledge, align content with buyer intent rather than campaign logic, and connect content, data and orchestration more deliberately. Linear funnels and campaign-led journeys struggle to reflect how buyers actually navigate information today. The challenge for marketing leaders is no longer how to push content more efficiently, but how to remain relevant inside AI-mediated discovery processes they do not fully control. 

        These shifts raise practical questions many teams are only beginning to confront. How do AI systems decide which sources to trust? What makes content discoverable in agent-driven environments? And how should go-to-market strategies adapt when discovery happens long before engagement? 

        Ornella Urso - Research Director, IDC Retail Insights - IDC

        Analyst Profile
        Ornella Urso is Head of IDC's Retail Insights team and leads the Customer Experience research group in Europe. Urso conducts market research, industry analysis, and proactively contributes to the definition of thought-leadership at the intersection of businesses priorities and technology innovation in B2C and D2C strategy companies. In her role, she is responsible for the delivery of research reports, custom projects and offers strategic direction and advice to both technology providers and IT and business executives of global brands.