Last week, I served up my reflections on 2025: a year that transformed content operations from a back-office function into a strategic capability. Today, I'm putting on my chef's hat and making predictions about what's cooking in 2026.
Fair warning: Some of these predictions will age like fine wine. Others might age like milk. But that's the fun of putting stakes in the ground.
Let's see what the content operations kitchen has in store for us.
Prediction #1: 2026 is The Year of the AI Agent (For Real This Time)
The Bold Prediction:
By the end of 2026, 70% of enterprise DAM and Content Hub implementations will have at least 3 production AI agents handling routine tasks autonomously. I'm not talking about just AI-assisted features, but true agentic AI making decisions and taking actions.
Why This Will Happen:
The math is compelling. According to recent industry research:
- AI-powered content creation market is growing at 19.4% CAGR ($2.15B in 2024 → $10.6B by 2033)
- 73% of CIOs surveyed by Gartner increased AI funding in 2024, and that momentum continues
- Content operations teams face 44% more pressure to scale output while maintaining personalization (Adobe 2025 Digital Trends report)
But here's what's different in 2026: The infrastructure is finally ready.
In 2025, we experimented with AI agents. In 2026, vendors like Aprimo, Bynder, Sitecore, and others will ship AI agents as core platform features, not experimental add-ons.
What This Looks Like in Practice:
The Metadata Agent:
- Uploads a batch of 500 product images
- AI agent analyzes each image (objects, colors, context, brand elements)
- Automatically populates 15-20 metadata fields
- Organizes into collections based on product categories, seasons, campaigns
- Flags potential brand guideline violations
- All within seconds of upload
The Workflow Orchestration Agent:
- New campaign creative comes in
- Agent evaluates complexity, rights requirements, stakeholders needed
- Automatically routes to appropriate reviewers based on workload, expertise, availability
- Escalates when SLAs are at risk
- Learns from outcomes to improve future routing
The Quality Assurance Agent:
- Continuously scans asset library
- Identifies assets with expiring rights, missing metadata, broken links
- Proactively alerts stakeholders
- Suggests remediation actions
- Generates compliance reports automatically
What You Should Do Now:
- Audit your metadata model. AI agents are only as good as the structure they work within.
- Document your workflows. Before automating, clarify what should happen.
- Start small. Pilot one agent on one use case before scaling.
- Measure everything. Track time saved, error rates, user satisfaction.
The Contrarian Take:
Don't automate garbage processes. If your workflow is already broken, an AI agent will just execute broken faster. Fix the process first, then automate.
Prediction #2: Content Operations Gets Its Own Seat at the Leadership Table
The Bold Prediction:
In 2026, we'll see 100+ "Chief Content Officer" or "VP of Content Operations" appointments at mid-to-large enterprises. These won't be rebranded CMO roles, but distinct positions focused on the content supply chain.
Why This Will Happen:
Content operations is having its "supply chain management" moment.
Twenty years ago, supply chain was a back-office concern. Then companies realized that logistics, inventory management, and supplier coordination were strategic differentiators. Supply chain leaders joined the C-suite.
Content operations is following the same trajectory:
- Complexity is exploding: Average enterprise manages 300,000+ digital assets across 20+ channels
- Speed is critical: Time-to-market for content decreased from weeks to days to hours
- Risk is real: Brand consistency, rights management, compliance issues cost millions when mismanaged
- Technology spend is significant: DAM, PIM, workflow, AI tools represent 7-figure investments
This requires dedicated leadership.
What This Role Looks Like:
The Chief Content Officer (or VP of Content Operations) owns:
- Strategy: Content operations maturity roadmap
- Technology: DAM, PIM, workflow, AI agent platforms
- Process: Workflows, governance, quality standards
- People: Content operations team (often 10-50 people in large orgs)
- Metrics: Time-to-market, asset utilization, cost per asset, workflow efficiency
This is distinct from:
- CMO: Owns marketing strategy and brand
- CTO: Owns IT infrastructure and engineering
- CDO (Chief Digital Officer): Owns digital transformation broadly
What You Should Do Now:
If you're positioning yourself for this kind of role:
- Build cross-functional fluency: Technology + process + people + strategy
- Document business impact: ROI of every content ops initiative
- Network with executives: CMOs, CTOs, COOs who deal with content at scale
- Develop frameworks: Maturity models, evaluation criteria, governance templates
If you're hiring for your organization:
- Look for hybrid skills: You need someone who is not just technical and not just strategic, but both.
- Prioritize change management: Technology is easy; adoption is hard.
- Find someone with vendor independence: They should recommend the best tools, not just their favorite tools.
The Contrarian Take:
Some organizations will try to bolt content operations onto existing roles (CMO + content ops, CTO + content ops). This will work for smaller companies. For enterprises, it will fail because the role needs dedicated focus.
Prediction #3: The Great DAM/PIM/CMS Integration Wars Begin
The Bold Prediction:
In 2026, every major content platform will position itself as the "central hub" for content operations, leading to brutal competition and, ironically, better integrations.
Why This Will Happen:
Right now, we have:
- DAM vendors (Bynder, Aprimo, Content Hub) saying: "We're your content hub. PIM and CMS should integrate with us."
- PIM vendors (Akeneo, Pimcore, Salsify) saying: "We're your product content hub. DAM and commerce should integrate with us."
- CMS vendors (Sitecore XM Cloud, Adobe Experience Manager, Contentful) saying: "We're your experience hub. Everything should feed us."
Everyone wants to be the center of the content universe.
In 2026, this competition will intensify, forcing vendors to:
- Build better integrations (because customers demand it)
- Create more open APIs (because walled gardens lose)
- Develop clear positioning (because "we do everything" convinces no one)
What This Looks Like in Practice:
The Integration Layer Emerges:
Organizations will stop trying to choose one central system and instead build orchestration layers that treat all systems as peers:
- DAM → Marketing assets, brand guidelines, creative files
- PIM → Product data, specifications, relationships
- CMS → Web content, experience fragments, page components
- Workflow → Orchestration across all systems
- AI → Intelligence layer that spans everything
Think of it like a restaurant kitchen:
- DAM is the pantry (ingredients/assets)
- PIM is the recipe book (product structure)
- CMS is the plating station (experience assembly)
- Workflow is the expediter (making sure orders go out right)
- AI is the sous chef (helping everywhere)
The Composable Architecture Reality Check:
MACH architecture (Microservices, API-first, Cloud-native, Headless) will move from hype to practice.
The winners will be organizations that understand:
- Composability isn't about buying dozens of point solutions
- It's about deliberately choosing best-of-breed tools that integrate well
- And having the orchestration capability to make them work together
What You Should Do Now:
- Map your content supply chain. Document every system, every hand-off.
- Identify your true "system of record" for assets (probably DAM), for product content (probably PIM), and for web content (probably CMS).
- Invest in integration infrastructure: APIs, iPaaS tools, data synchronization.
- Choose vendors who play nice. Look for open APIs, documented integration patterns, and partner ecosystems.
The Contrarian Take:
Some organizations will get drunk on composability Kool-Aid and end up with 30 systems that barely talk to each other. Composable doesn't mean complicated. Start with 3-5 core systems that integrate excellently before adding more.
Prediction #4: Data Quality Becomes the #1 Content Operations Bottleneck
The Bold Prediction:
By mid-2026, 60% of content operations initiatives will be delayed or derailed not by technology limitations, but by poor data quality. This means bad metadata, inconsistent taxonomy, and unclear content models.
Why This Will Happen:
AI agents are like master chefs: Give them quality ingredients (good data), and they'll create magic. Give them garbage ingredients (bad data), and even the best chef can't save the dish.
The AI agent revolution of 2026 will expose every data quality problem organizations have been ignoring:
The Metadata Mess:
- Inconsistent tagging ("Q4-Campaign" vs "Q4_campaign" vs "campaign-q4")
- Missing required fields (50% of assets lack ownership info)
- Outdated values (still tagging with 2023 product names)
- No governance (everyone invents their own tags)
The Taxonomy Tangle:
- Multiple competing classification schemes
- No clear hierarchy or relationships
- Regional variations without mapping
- No one owns it or maintains it
The Content Model Confusion:
- Asset types not clearly defined
- Attributes inconsistently applied
- Relationships not modeled
- No versioning strategy
AI agents can't fix structural problems; they amplify them.
What This Looks Like in Practice:
Scenario: The Failed AI Metadata Agent
Organization implements AI agent to auto-tag product images. Sounds great!
But:
- Product taxonomy has 3 competing structures (marketing's, e-commerce's, product team's)
- Color values are inconsistent ("Red" vs "RED" vs "Crimson" vs "Ruby")
- Product categories changed 6 months ago, but 30,000 old assets never got updated
- No clear owner of the taxonomy
Result: AI agent creates more chaos because it doesn't know which structure to follow.
Scenario: The Successful Data Foundation Project
Same organization, different approach:
- Audit current state. Document every taxonomy, identify overlaps and gaps.
- Establish governance. Appoint taxonomy owner, create change management process.
- Rationalize structures. Create ONE product taxonomy with clear mappings from old systems.
- Clean existing data. Fix the 30,000 assets (painful but necessary).
- THEN deploy AI agent. Now it has a clean foundation to work from.
Result: AI agent saves 40 hours per week of manual tagging work with 95%+ accuracy.
What You Should Do Now:
Q1 2026 Priority: Data Foundation Audit
- Metadata audit:
- What fields exist?
- Which are actually used (vs empty)?
- What's the quality/consistency?
- Who maintains them?
- Taxonomy review:
- Document all classification schemes
- Identify conflicts and redundancies
- Map relationships
- Assign ownership
- Content model evaluation:
- Asset types clearly defined?
- Attributes consistently applied?
- Relationships properly modeled?
- Governance establishment:
- Who approves taxonomy changes?
- How do we maintain quality?
- What are the update processes?
Budget 3-6 months for this work. It's not sexy. It won't make for great marketing case studies. But it's the foundation everything else depends on.
The Contrarian Take:
Some vendors will promise AI can "fix your data quality automatically." It can't. AI can help clean data once you define what "clean" means. But humans have to establish the rules, structures, and governance. There's no shortcut.
Prediction #5: Sitecore Makes a Major Agentic AI Announcement (and It's Actually Good)
The Bold Prediction:
Sitecore will launch a comprehensive agentic AI framework across Content Hub, XM Cloud, and other products. This will go beyond isolated AI features to create a coordinated AI agent ecosystem. And surprisingly, they'll actually execute well.
Why This Will Happen:
Sitecore has been quietly building toward this:
Recent Signals:
- Agent API launch for XM Cloud (content operations via AI)
- Marketer MCP integration (Model Context Protocol for tool access)
- AXP (Agentic Experience Platform) vision announced
- Agentic Studio for building custom agent flows
- Strong partnership with Anthropic and other AI providers
In 2026, these pieces will come together into a coherent story: "Sitecore: The Agentic Content Operations Platform"
What This Could Look Like:
The Content Hub AI Agent Framework:
- Metadata Agent: Auto-enrichment based on company-specific taxonomy
- Rights Management Agent: Proactive expiration tracking and renewal workflows
- Creative Ops Agent: Automated briefing, routing, and asset delivery
- Analytics Agent: Insight generation and optimization recommendations
The XM Cloud AI Agent Framework:
- Personalization Agent: Dynamic experience assembly based on visitor context
- Content Optimization Agent: A/B testing automation and winner declaration
- Content Creation Agent: Generate page variants, headlines, copy (with human approval)
The Cross-Product Agent Orchestra:
- Agents that span Content Hub and XM Cloud
- Approved brand assets from Content Hub automatically available in XM Cloud
- Performance data from XM Cloud feeding back to Content Hub for asset scoring
- Unified governance and compliance across both platforms
Why This Will Work (Unlike Some Past Sitecore Launches):
- Market demand is clear. Every client I talk to wants this.
- Technology is mature. AI agent frameworks are proven now.
- Competition is fierce. Adobe, Acquia, and others are building similar.
- Sitecore has strong partnerships. Anthropic, Microsoft, and others provide the foundation.
What You Should Do Now:
- Attend Sitecore events, like Symposium 2026 and SUGCON sessions.
- Join beta programs to get early access to agentic features.
- Prepare your data (See Prediction #4).
- Build use case library. Ask where would agents add most value.
The Contrarian Take:
There's a non-zero chance Sitecore over-promises and under-delivers (historical precedent exists). Don't rip out working systems based on roadmap promises. Wait for production releases and customer references before betting your architecture on it.
Prediction #6: The Skills Gap Widens (Then Starts to Close)
The Bold Prediction:
In 2026, demand for content operations talent will exceed supply by 300%, driving salaries up 25-40% for qualified professionals. By Q4, we'll see the first wave of training programs and certifications trying to close the gap.
Why This Will Happen:
The Supply Side:
- Not enough people with combined skills: DAM/PIM tech + AI understanding + strategic thinking
- Traditional marketing ops people lack technical depth
- Traditional developers lack content operations understanding
- Universities aren't teaching "Content Operations" as a discipline yet
The Demand Side:
- Every mid-to-large enterprise needs content operations capability
- AI agent implementations require specialized knowledge
- Composable architecture projects need integration expertise
- Leadership roles (see Prediction #2) need to be filled
What This Creates:
- Talent wars: Organizations poaching from each other
- Compensation inflation: VP-level content ops roles paying $180K-250K+ in major markets
- Consultant boom: Independent practitioners charging $200-300/hour
- Training gap: Desperate need for education programs
What This Looks Like in Practice:
The Hot Skills in 2026:
- Technical Foundation:
- DAM/PIM platform expertise (Content Hub, Bynder, Aprimo, Akeneo, etc.)
- API integration and iPaaS tools
- AI/ML fundamentals (not deep learning, but practical application)
- React/TypeScript for platform customization
- Strategic Capabilities:
- Content operations maturity assessment
- Vendor selection and evaluation
- Change management and user adoption
- ROI modeling and business case development
- Hybrid Skills:
- Translate between technical and business stakeholders
- Design AI agent workflows
- Build governance frameworks
- Facilitate cross-functional workshops
The people who have all three? Unicorns. And they'll be paid accordingly.
The Certification and Training Boom:
By Q4 2026, we'll see:
- Vendor certifications expanding: Sitecore, Bynder, Aprimo all launching advanced content ops certs
- Independent training programs: Content operations bootcamps and courses
- University programs piloting: First "Content Operations" concentrations in digital marketing programs
- Community-led education: Practitioners creating courses and mentorship programs
(Full disclosure: I'll likely be part of this with my own certification program. The need is too great not to contribute.)
What You Should Do Now:
If you're a practitioner:
- Build portfolio of work. Document implementations, show business impact.
- Get certified in the major platforms you work with.
- Learn adjacent skills. If you're a DAM expert, learn PIM; if you're technical, learn strategy.
- Build in public. Blog, speak, and share what you learn.
- Position for leadership. Think beyond implementation to architecture.
If you're hiring:
- Hire for potential, not perfect match. The "perfect" candidate doesn't exist.
- Build internal training. Grow talent rather than only buying it.
- Create career paths. Content operations should be a destination, not a waypoint.
- Compensate competitively. You'll lose talent if you don't.
The Contrarian Take:
Some of the skills inflation will be temporary. As more people enter the field and tools become more user-friendly, the "premium" for content operations expertise will moderate. But the underlying demand is real and will persist for years.
Prediction #7: Content Operations Performance Metrics Go Mainstream
The Bold Prediction:
By end of 2026, 75% of enterprise content operations teams will have dashboard reporting on standardized KPIs. This is a move from "we don't measure this" to "we optimize against these metrics weekly."
Why This Will Happen:
You can't manage what you don't measure. And executives are tired of content operations being a black box.
With AI agents and better integration, measurement becomes feasible:
The Core Content Operations Metrics That Will Emerge:
Efficiency Metrics:
- Time-to-Market: Average time from creative brief to asset delivery
- Target: Reduce by 40% over baseline
- Cost per Asset: Fully-loaded cost to create and manage one asset
- Target: Decrease while maintaining quality
- Asset Utilization Rate: % of assets actually used vs created
- Target: >60% (anything lower suggests waste)
- Workflow Cycle Time: Time assets spend in each workflow stage
- Target: Identify and eliminate bottlenecks
Quality Metrics:
- Metadata Completeness: % of required fields populated
- Target: >95%
- Compliance Rate: % of assets meeting brand/legal requirements
- Target: 100% (nothing else acceptable)
- Search Success Rate: % of searches that find relevant assets
- Target: >85%
- Rights Management Coverage: % of assets with clear, current rights
- Target: 100%
Business Impact Metrics:
- Asset Reuse Rate: How often assets are repurposed
- Target: Maximize (reduces creation costs)
- Campaign Launch Speed: Time to market for new campaigns
- Target: Continuously improve
- Cross-Channel Consistency: Brand alignment across touchpoints
- Target: >90% consistency scores
- ROI on Content Operations Technology: Value delivered vs investment
- Target: 3-5x return
What This Looks Like in Practice:
The Content Operations Dashboard (2026 Edition):
Weekly review meeting:
- Speed: We reduced average time-to-market from 12 days to 8 days (33% improvement)
- Cost: Cost per asset dropped from $850 to $720 (AI agent automation helped)
- Quality: Metadata completeness up from 78% to 94% (AI agent + better governance)
- Impact: Asset reuse rate increased from 42% to 59% (better findability)
Actions from data:
- Workflow stage "Legal Review" is the bottleneck (average 4.2 days). Implementing AI-assisted pre-check to flag issues earlier.
- Product category "Electronics" has 67% metadata completeness vs 95% org average. Assigned owner to fix.
- Campaign assets created for "Spring Launch" had 89% utilization vs 56% average. Document what made this successful, replicate.
What You Should Do Now:
- Define your baseline. Measure current state, even if it's rough.
- Pick 5-7 core metrics. Don't boil the ocean.
- Establish measurement systems. How will you actually track this?
- Set improvement targets, like 10-30% improvement year-over-year.
- Review regularly: monthly at minimum, weekly for high-velocity teams.
The Contrarian Take:
Some teams will get lost in measurement and forget to actually improve things. Metrics are means to an end, not the end itself. Measure what matters, but don't measure everything.
The Wild Card Predictions (30% Confidence, But Fun)
Wild Card #1: A Major Tech Company Acquires a Leading DAM Vendor
Microsoft, Salesforce, or Adobe makes a major acquisition (Bynder? Aprimo? Someone else?). Rationale: Content operations becomes too strategic to leave to independent vendors.
Wild Card #2: The First "Content Operations Unicorn" Emerges
A startup building AI-first content operations platform raises at $1B+ valuation. Rationale: Market is huge, incumbents are vulnerable, right product at right time.
Wild Card #3: Sitecore Spins Off Content Hub
Sitecore separates Content Hub into its own business unit or spins it off entirely, allowing it to serve non-Sitecore CMS customers more effectively. Rationale: Product has become too big and strategically important to be just one part of Sitecore.
Wild Card #4: European Data Regulations Reshape Content Operations
New EU regulations on AI training data and content rights force significant changes to how DAM systems handle licensing, attribution, and consent. Rationale: Regulatory pressure is increasing, content operations intersects with compliance.
What You Should Do in Q1 2026
Based on these predictions, here's my advice for the first quarter:
For Content Operations Practitioners:
- Skill up on AI agents. Take courses, read documentation, build proof-of-concepts.
- Document your wins. A portfolio of successful implementations matters more than titles.
- Network actively. The talent shortage means opportunities are everywhere.
- Think strategically. Move beyond "how to implement" to "what to implement and why."
For Content Operations Leaders:
- Audit data foundation. Start now; it takes months.
- Establish KPIs. Define what success looks like.
- Pilot AI agents. Use small, contained use cases to learn.
- Build your team. Hiring will get harder, so start early.
- Create career paths. Retain talent by showing growth opportunities.
For Technology Vendors:
- Build better integrations. Customers will demand it.
- Ship agent frameworks. This means not just AI features, but true agentic capabilities.
- Invest in education. Help customers succeed at scale.
- Be honest about AI. Over-promising creates backlash.
For Everyone:
Watch for vendors and practitioners who can bridge technology and strategy. That's where the value is. The future of content operations isn't just better tools; it's better orchestration of people, process, and technology.
Final Thoughts: Embracing the Mistaken Orders
When I started this blog, the "mistaken orders" metaphor was about navigating Sitecore Content Hub's transition to React. This was something that felt confusing and wrong at first but turned out to be essential.
The same applies to 2026's changes:
- AI agents might feel like giving up control (they're not; they're scaling your judgment)
- Data governance work might feel like bureaucracy (it's not; it's the foundation for everything)
- New leadership structures might feel like organizational complexity (they're not; they're recognition of strategic importance)
The organizations that succeed in 2026 will be the ones that embrace the "mistaken order" moments. These are the ones that lean into changes that feel uncomfortable but are ultimately necessary.
Let's Connect
These predictions are based on my work with enterprise clients, conversations with industry leaders, and analysis of market trends. But I'd love to hear your perspective:
What do you think will happen in 2026? Which predictions do you agree/disagree with? What am I missing?
Drop a comment below or reach out on LinkedIn. And if you want weekly insights on content operations, AI, and Sitecore Content Hub, subscribe to my newsletter.
Here's to an exciting 2026. May your metadata be clean, your workflows efficient, and your AI agents helpful.
Bon appétit,
Roel van Roozendaal Chief Chef of Mistaken Orders
P.S. Come back to this post in December 2026. Let's see how many I got right. I'm aiming for 5 out of 7 (the wild cards don't count; that's why they're wild cards).
P.P.S. If you're looking to level up your content operations capabilities in 2026, I'm planning some new offerings. Stay tuned to the newsletter for announcements.