Activating Acquia AI · consulting & services

Acquia gave you the AI. We make it pay off.

DAM, CDP, Site Studio, Campaign Studio — it’s already in your stack. CXO turns Acquia’s AI from switched-on to operationalized: content that tags, translates and routes itself, personalization that runs, search that stays answerable to AI. Measurable outcomes from features you already own — and a foundation ready for the 2026 agents.

See where the value actually comes from
The activation gap

Almost every organization has rolled out AI. Few can prove it’s working.

The gap isn’t the technology — it’s everything around it. Across organizations, adoption is near-universal; measurable value is the exception. The ones that close the gap don’t buy more AI — they operationalize what they already have.

Gen-AI pilots with no measurable business impact~95%Gen-AI pilots delivering measurable value~5%

Among enterprise gen-AI initiatives.1

42%
of organizations have scrapped most of their AI initiatives — up from 17% a year earlier2
60%
of AI projects will be abandoned through 2026 for lack of AI-ready data3
~2×
the success rate when AI is delivered with a specialized partner vs. built in-house4
From licensed to agent-ready

Most teams are stuck on the first rung. The value lives higher up.

Activating Acquia AI is a climb, not a switch. Here’s the path — and where the measurable value (and readiness for Acquia’s 2026 agents) actually starts.

01
Licensed

Paying for AI features you haven’t switched on.

02
Switched on

Features enabled — but generic output and no workflow fit.

03
Operationalized

AI wired into your content ops, governed, delivering measurable value.

04
Agent-ready

Clean foundation and governance — ready for Acquia’s 2026 DAM agents, with human checkpoints in place.

Most teams stall hereWhere measurable value lives →
What activation actually takes

We do the unglamorous work that makes the AI pay off.

Acquia is blunt about it: the AI rewards a clean foundation. We build that foundation and wire the features into how your team actually works.

Foundation — taxonomy, metadata, rights and governance, the framework Acquia’s AI and agents need to work at all.
Activation — we switch on and configure the features that fit your use cases. Not every feature; the ones that move outcomes.
Operationalization — AI wired into your editorial, campaign and DAM workflows, so it’s part of how work ships, not a side tool.
Measurement — we define the outcomes and prove ROI against the real total cost of running AI, not just hours saved.
Agent-readiness — we prepare your library and governance for Acquia’s 2026 DAM agents. The foundation is yours; the maintenance becomes theirs.

More on how we think about this: what “agentic” really means in production →  ·  see how our pods deliver →

The AI you already own

The Acquia AI surface — activated, not dormant.

A map of where AI already lives across your Acquia stack — and what we switch on, govern, and operationalize.

Acquia DAM AI

Auto-tagging, natural-language search, AI alt-text and captions, the AI Copilot and Video Creator — switched on against a clean, governed library.

DAM
DAM AI agents

The Curator and The Guardian (2026): metadata enrichment, rights and compliance, kept clean as volume scales — we get the foundation ready.

2026
Acquia CDP & ML Studio

Custom models, scores and audiences surfaced and operationalized into campaigns and analytics — not left sitting in the data layer.

CDP
Personalization & Campaign Studio

AI-assisted segments and journeys wired into multichannel campaigns — activated, measured, tuned.

Campaign
Site Studio & components

A governed, AI-assisted component system — design tokens, accessibility and brand built in.

Site Studio
Search & GEO

Structured content and retrieval so your experience stays answerable by AI search and assistants.

This is the surface we activate — explore the full set of capabilities →

The economics

Where AI pays off — and where it doesn’t.

Switching on every feature isn’t the win. AI is far cheaper for high-volume, repetitive work — and the wrong tool everywhere else. Activated blindly, it can quietly cost more than the work it replaced.

AI pays off
  • Auto-tagging & metadata at library scale
  • Alt-text, transcripts and captions
  • Translation and content variants
  • Search indexing and structured output
Acquia DAM: metadata ~100× faster, ~90% lower cost5
Keep it human
  • Low-volume, one-off or highly variable work
  • Brand voice, narrative and strategy
  • Sensitive, regulated or high-stakes content
  • Final judgment, sign-off and the call that matters
Automate everything and the math flips: tokens, licensing, maintenance and oversight add up. Gartner calls it the AI cost paradox — past a point, a fully-automated operation can cost more to run than the team it replaced.6

We point AI at the work where it actually saves money, size the true total cost — tokens, upkeep and oversight included — and leave the rest to your team. Activation that pays off, not a bigger bill.

Control & governance

Automated, not unsupervised.

Going all-in on automation is its own risk. Audiences trust AI-made work less, agents still get things wrong, and one bad output at scale becomes a brand or compliance problem fast. The teams that win don’t remove people — they put them at the right decision points.

01 · MANUAL
People do the work
Full control, full cost. Right for low-volume, high-stakes, or brand-defining work.
02 · AI-ASSISTED
AI drafts, people decide
AI handles the volume; people review and approve before it ships. The everyday default for most content ops.
03 · GOVERNED-AUTONOMOUS
AI runs, people set the rules
AI acts within guardrails, monitored and audited. Reserved for well-understood, low-risk, high-volume tasks.

CXO sets the mode per task, by risk — more oversight where a mistake costs more.

When audiences detect AI, ~4× as many lose trust as gain it7
AI agents still fail ~70% of multi-step tasks in testing8

We design the governance — what runs automatically, what needs a human to approve, audit trails, and brand and rights guardrails — so AI scales without the blast radius. AI assists; your team stays in control.

AI in delivery

We don’t just activate AI. We build with it.

Activating Acquia’s features is one kind of AI. The other is how your build gets made — much of an Acquia project is still custom code: modules, integrations, migrations, theming. We apply AI across our SDLC to engineer and maintain it, so releases ship faster, hold to Drupal and Acquia standards, and stay well-documented. All human-reviewed — governed exactly as above.

Faster delivery — AI-assisted scaffolding, code and tests across the SDLC mean more shipped per sprint, without trading away quality.
To standard, by default — AI-assisted review catches issues early and holds your codebase to Drupal and Acquia best practice.
Documented as it ships — specs, commit hygiene and engineering knowledge stay current, so your build doesn’t become a black box.

Same discipline as your features: AI assists, our engineers judge.

Why cxontology

Senior, accountable, and built for digital experience — not a body shop, not a black box.

Activating Acquia AI is one of the ways we help. cxontology is a digital experience engineering, go-to-market and AI partner — a senior team that works across the digital maturity curve, with the foundation work and accountability this kind of activation needs. More about how we work →

Three pillars, one team

Digital experience engineering, go-to-market, and AI & agentic activation — across the maturity curve, not a single point tool.

See all capabilities →
A senior pod, a named lead

A dedicated pod with a Pod Leader who owns your engagement — senior practitioners and direct access, not layers or juniors by default.

How we deliver →
Proof in the open

Perspectives from active engagements, and assessments that put your digital operation in context against your peers.

Read our insights →

25+ specialists across Chicago, Austin & Chennai  ·  150+ projects delivered

We didn’t need more AI tools. We needed someone to make the ones already in Acquia work in our process. CXO cleaned up our DAM foundation and wired the AI in — now it delivers instead of just demoing.
VP, Digital ExperienceGlobal B2B manufacturer
Get a baseline

See how ready your Acquia ecosystem is to activate AI.

Enter your URL for a pro-bono Acquia AI activation read. Our team reads your site using publicly discoverable signals and sends back a clear view of which AI features you’re likely paying for but not using, how clean your foundation is, the highest-value places to switch on first, and how ready you are for the 2026 agent wave.

Let’s talk

Sitting on Acquia AI you’re not using? Let’s put it to work.

From cleaning the foundation to switching on the right features and operationalizing them — we’d like to know where you are with Acquia AI and how we can help. Email us or submit this form and a member of our team will reach out to you soon!

sales@cxontology.com

We won’t use this data for marketing or share it with third parties.

Sources & notes
  1. 1 MIT NANDA initiative, The GenAI Divide: State of AI in Business (2025): roughly 95% of enterprise generative-AI pilots showed no measurable P&L impact; about 5% drove rapid value. Based on 150 executive interviews, 350 employee surveys and 300 public deployments.
  2. 2 S&P Global Market Intelligence (2025), survey of 1,000+ organizations across North America and Europe: 42% had scrapped most of their AI initiatives, up from 17% the prior year.
  3. 3 Gartner: an estimated 60% of AI projects will be abandoned through 2026 for lack of AI-ready data. AI-ready data = data aligned to the specific use case, actively governed, and quality-assured.
  4. 4 MIT NANDA (2025): AI initiatives delivered via purchase or partnership succeeded about 67% of the time, versus roughly 33% for internal builds — about twice the rate.
  5. 5 Acquia DAM product materials: AI-generated metadata cited at roughly 100× faster than manual processing and about 90% lower cost — a vendor figure for that task.
  6. 6 Gartner, The State of the Human-AI Workforce in Service and Support: as automation approaches ~50% of an estate, licensing, specialized labor and usage costs can exceed frontline savings — an “AI cost paradox” in which a GenAI-powered operation may cost more than the equivalent human workforce once total cost of ownership is counted.
  7. 7 Klaviyo/Datalily (2025): when consumers detect AI in marketing, 31% reported reduced trust vs. 7% increased (about 4 to 1). Canva (2026): 78% would rather see human-made ads.
  8. 8 Reported agentic-AI simulation testing (2025–2026): AI agents fail multi-step tasks nearly 70% of the time.

These figures describe the broader enterprise-AI market and are cited as industry context, not cxontology results.