Unprompted: The AI Tools Are Here. Does Your Team Know If They're Working?
Key Highlights
- AI adoption is high, but effective use is not: 80% of employees are using AI tools, yet only 3% are using them in the productivity “sweet spot.”
- The capability jump is real: Google Ads, Photoshop, Microsoft 365 and Claude are all making AI more embedded, faster and easier to use inside everyday marketing workflows.
- More tools will not fix weak operations: Without clear success metrics, governance and review checkpoints, new AI capabilities can widen the measurement gap instead of improving results.
- The teams pulling ahead are not the ones with the most AI tools; they are the ones that can measure what is working, standardize workflows and redirect time toward higher-value work.
Welcome to Unprompted: The AI Marketing Brief, where I cut through the noise in AI news and research to show marketers what’s happening — and why it matters for your work, your team and your career.
Here's the data point that should be on every marketing leader's whiteboard right now: 80% adoption, 3% productivity sweet spot.
That’s not a typo. ActivTrak analyzed 443 million hours of behavioral work data and found that while the vast majority of employees are using AI tools, almost none of them are using AI in the way that actually moves the needle.
That's the uncomfortable backdrop for an Unprompted edition packed with genuinely impressive capability announcements. Video generation is baked directly into Google Ads. Natural language editing landing in Photoshop. Agentic task execution across Microsoft 365. Reusable one-click workflows in Excel and PowerPoint. These are real, and they're worth your attention.
But here's the thing: Tools don't close a measurement gap. They widen it if your team doesn't know what good looks like before the new capability arrives. The organizations pulling ahead right now aren't the ones with the most tools. They're the ones who can actually answer the question: Is this working?
Copilot Cowork: A new way of getting work done
Author: Charles Lamanna
Website: Microsoft 365 Blog
Just the Facts: Copilot Cowork is a new feature integrated into Microsoft 365 Copilot that enables the AI to take action across Microsoft 365 applications rather than only providing conversational responses. When delegated a task, Cowork creates a plan with clear checkpoints for user approval before executing actions across Outlook, Teams, Excel, and other Microsoft 365 apps, allowing users to confirm, modify or pause execution at any time. The feature is currently in Research Preview with select customers and will be more broadly available through the Frontier program in late March 2026.
Why It Matters to Marketers:
- Cowork handles multistep tasks (calendar cleanup, meeting prep, competitive research, launch planning) in parallel, freeing marketers to focus on strategic thinking and client-facing work instead of assembly-line admin tasks.
- The ability to delegate research, document generation, deck creation and asset packaging within a single workflow signals a shift toward AI agents handling content-production infrastructure — marketers should expect fewer bottlenecks in collateral production timelines but face pressure to oversee AI-generated quality.
- Cowork operates within approval checkpoints and cannot execute without user confirmation, meaning marketers must build review capacity into workflows and establish clear quality standards before delegation, as execution speed without governance creates risk.
- Integration with the Microsoft 365 ecosystem (Outlook, Teams, Excel, SharePoint) creates a stronger incentive for marketing teams already using these tools to stay in-house rather than adopting specialized marketing automation platforms, potentially affecting technology stack choices and vendor negotiation power.
Adobe is debuting an AI assistant for Photoshop
Author: Ivan Mehta
Website: TechCrunch
Just the Facts: Adobe's AI assistant for Photoshop is rolling out in beta to web and mobile app users, allowing users to remove objects, change colors, adjust lighting, add effects and transform backgrounds through natural language prompts. Adobe is also launching AI Markup, a public beta feature enabling users to draw on-screen markers that the AI assistant transforms into edits, and expanding its Firefly media generation tool with Generative Fill, Generative Remove, Generative Expand, Generative Upscale, and one-click background removal capabilities. The company has previously announced unlimited generations for Firefly subscribers and integrated over 25 third-party video and image generation models into the platform.
Why It Matters to Marketers:
- Marketers using Photoshop for ad creative, social assets and landing page imagery can now delegate labor-intensive edits (background swaps, object removal, color adjustments) directly within their existing workflow, compressing creative production timelines and reducing dependency on design teams for routine modifications.
- Free users' 20-generation monthly allowance and paid users' unlimited access signals Adobe's bet on lowering barriers to visual asset creation for non-designers — marketing teams may increasingly own image editing tasks, reshaping collaboration models between content, creative and demand gen functions.
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Adobe's integration of 25+ external models (Google, OpenAI, Runway, Black Forest Labs) creates vendor lock-in complexity; marketers need clarity on which models drive which outputs and how model switching affects asset consistency, quality and IP considerations as Adobe's feature set expands unpredictably.
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Unlimited generations and one-click automation may encourage rapid asset production without governance; marketers should establish review checkpoints and enforce brand guidelines before delegating image editing to AI to avoid visual inconsistencies, off-brand outputs or unintended edits in published assets.
Advancing Claude for Excel and PowerPoint
Website: Claude Blog
Just the Facts: Claude for Excel and PowerPoint now share full conversation context across all open files, allowing Claude to read cell values, write formulas, merge datasets and edit slides while maintaining continuity without requiring users to re-explain tasks between applications. Skills — reusable one-click workflows — are now available inside both add-ins, with preloaded starter skills for financial analysis (model auditing, LBO/DCF templates, comparable company analysis, data cleaning) and presentation work (competitive landscape decks, deck updates, investment banking reviews). Claude for Excel and PowerPoint are now deployable through Amazon Bedrock, Google Cloud's Vertex AI and Microsoft Foundry, and the tools are available in beta to all Mac and Windows users on paid plans.
Why It Matters to Marketers:
- Context carryover between Excel and PowerPoint eliminates manual data re-entry and re-explanation when building decks from analysis, enabling faster turnaround on data-driven content and reducing friction between analytics and creative teams during collateral production.
- Skills codify institutional workflows (data cleaning, competitive analysis, deck formatting) into one-click actions, addressing a core bottleneck in marketing operations. Teams can standardize processes across individuals and departments without rebuilding logic or training new staff repeatedly.
- Multi-cloud deployment options (Bedrock, Vertex AI, Foundry) allow organizations to route AI workloads through existing compliance and data residency frameworks, reducing blockers for enterprise adoption in regulated or privacy-sensitive organizations.
- Preloaded skills for comparable company analysis, variance auditing, and competitive intelligence directly serve demand gen and strategic marketing functions. These are high-effort, repetitive tasks that historically require external hiring or consulting, now delegable to AI with quality checkpoints embedded.
2026 State of the Workplace: AI Adoption & Performance Benchmarks
Website: ActivTrak
Just the Facts: ActivTrak's 2026 State of the Workplace report analyzes 443 million hours of behavioral work data across 1,111 organizations and 163,638 employees from 2023–2025, finding that AI adoption has reached 80% of employees with eightfold increase in time spent in AI tools, yet only 3% of users fall within the identified productivity sweet spot of 7–10% of total work hours in AI.
The report identifies a structural shift where workdays have shortened 2% and productive hours increased 5%, but focus efficiency has declined to 60% (a three-year low), collaboration has surged 34%, and disengagement risk has jumped 23% as freed-up capacity from reduced burnout is not being actively redeployed. This creates what the report frames as the "AI Measurement Gap," where organizations lack visibility into how AI adoption actually impacts productivity and workforce alignment. Weekend work has also become a structural feature, with Saturday productive hours jumping 46% and start times shifting 1 hour 24 minutes earlier year over year.
Why It Matters to Marketers:
- 80% adoption but only 3% in the productivity sweet spot signals that distributed AI tool sprawl (average of seven tools per org) creates governance gaps. Marketing teams implementing AI without measurement infrastructure face risk of siloed tooling, unclear ROI and lost operational coherence across campaigns and teams.
- With 23% of employees chronically under-challenged (vs. only 5% burned out), marketing departments must redesign role architecture and growth pathways post-AI adoption. Technical marketers, analysts and operators need visibility into expanded capacity and clear paths to higher-value work or face quiet attrition.
- Declining focus sessions (13m 7s, on average) and 34% surge in collaboration create friction for deep work. Content strategy, audience insight development and competitive analysis all require sustained focus; marketers must design async workflows and protected time blocks or accept lower-quality strategic output.
- 46% jump in Saturday hours and earlier start times reveal structural overwork disguised as "flexible" schedules. Marketing leaders should audit team weekend activity patterns and redefine success metrics to prevent burnout reemergence, especially among underutilized high-performers being asked to do more.
Resonate with the YouTube audiences that matter most to you, with Veo in Google Ads
Website: Accelerate with Google
Just the Facts: Google has integrated Veo, its generative video model, into Asset Studio within Google Ads, enabling advertisers to convert up to three static images into high-quality videos up to 10 seconds long with fluid, natural motion. Combined with Nano Banana (Google's image generation model), the tool allows advertisers to generate tailored, variation-rich creative assets at scale without a production crew. The generated videos can be packaged into customizable ad templates for Demand Gen and all campaign types. Google's internal data indicate that Demand Gen campaigns with at least three unique videos show significantly higher brand consideration and purchase intent lifts than campaigns with fewer video variations.
Why It Matters to Marketers:
- Marketers can now generate multiple video variations from a single asset in hours rather than weeks, enabling rapid, audience-specific creative iteration and "speed-of-culture" adaptation, eliminating production bottlenecks that historically required creative teams, freelancers or agencies to refresh video assets.
- Google's data on three-video minimum for Demand Gen effectiveness signals that creative diversity drives performance. Veo enables personalized audience segmentation at scale (per persona, subculture or cultural moment) rather than broad-audience campaigns, shifting power toward demand gen practitioners who can quickly test creative hypotheses.
- Generative video outputs may not align with brand guidelines, maintain tonal consistency or meet complex product positioning requirements. Marketers must establish review and approval workflows for AI-generated creative before deployment, especially in premium or regulated categories where authenticity and precision are non-negotiable.
- Native integration into Google Ads creates friction-free adoption but locks creative workflows into Google's models and templates. Advertisers lose flexibility to A/B test against external generative video tools and become dependent on Google's continuous model improvements and support for their primary creative production method.
About the Author
Alexis Gajewski
Contributor / AI Expert
Alexis Gajewski is the Associate Director of Newsroom Operations and Development at EndeavorB2B, where she leads editorial strategy and AI integration across a portfolio of 80+ B2B brands and 150 editors. With 18+ years in B2B media, she is best known for building the systems, training programs, and organizational infrastructure that help editorial teams operate at a higher level — faster, smarter, and with clearer standards.
Her expertise spans the full editorial stack — from SEO, GEO, and analytics to AI literacy, content strategy, and journalistic standards — with a particular focus on translating emerging technology into practical frameworks editorial teams can actually adopt. She designs and delivers training programs that meet teams where they are and build toward where the industry is going, with a specialty in AI integration that covers everything from foundational literacy to advanced workflows and agentic applications. A frequent guest on ASBPE webinars, Alexis is a recognized voice on the intersection of journalism and AI, and she writes for marketers, editors, and authors on how to thoughtfully and strategically implement AI practices.
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