Unprompted: The AI Marketing Brief — How AI Is Becoming Your Co-Worker

Welcome to Unprompted: The AI Marketing Brief, a series for marketers who want to know not just what is happening in AI, but why it matters. I track the news, research and developments shaping the AI landscape, then distill them into actionable insights for marketing professionals. Each edition highlights the shifts changing how we work, communicate and grow in our careers — helping you stay ahead in a world where AI is rewriting the rules. 

In this first edition, I’m sounding the alarm for marketers: AI is no longer just a tool for suggestions — it’s becoming a full-fledged co-worker. Anthropic’s Claude Cowork lets non-technical users hand off real tasks to AI agents, Google’s Gemini is transforming Gmail into a proactive, insight-driven inbox, and Apple is leaning on Gemini to supercharge Siri. Professionals are already using AI agents to tackle complex workflows, which makes one thing obvious: Marketing’s competitive edge won’t come from working harder — it will come from designing smarter systems, orchestrating AI alongside humans, and knowing how to turn autonomy into advantage. 

Claude Cowork, Explained: Everything to Know About Anthropic’s Answer to Claude Code for Normies

Author: Grant Harvey

Website: The Neuron 

Just the Facts: Anthropic has introduced Claude Cowork, a more approachable, general-purpose version of its “Claude Code” AI agent designed for non-technical users, currently available as a research preview for Claude Max subscribers. Instead of just chatting, Claude Cowork can autonomously reorganize files, generate spreadsheets or documents, and tackle work tasks by accessing a user-designated folder on your computer. This marks a shift from simple AI assistance toward agents that can execute work, signaling a broader industry move from advice to autonomous task completion. 

Why It Matters to Marketers: 

• Claude Cowork lowers the barrier to agent-style automation, meaning B2B teams can start delegating research, content prep, QA and analysis tasks without dedicated engineering support — forcing marketing ops leaders to rethink how work is assigned between humans and AI.
• As tools like Cowork abstract away code, the differentiator becomes prompt design, task scoping and oversight — pushing marketing leaders to upskill their teams in AI management and redefine roles around orchestration, not execution.
• AI coworkers can accelerate output, but they also complicate attribution and QA. Marketers will need clearer standards for validating AI-assisted work to avoid faster production masking weaker strategy or flawed data.
• If AI coworkers become embedded across functions, marketing’s competitive edge shifts from “who can produce more” to “who can design smarter systems,” rewarding teams that tightly align AI workflows with revenue metrics, customer insights and cross-functional goals. 

Gmail Is Entering the Gemini Era 

Author: Blake Barnes  

Website: Google Blog  

Just the Facts: Google is rolling out a major upgrade to Gmail, powered by its Gemini 3 AI model, that introduces tools to make email management smarter and more efficient. Key features include AI Overviews that summarize lengthy threads and answer natural-language questions, Help Me Write, Suggested Replies and Proofread to assist with composing and polishing messages, and an AI Inbox that highlights important content and tasks. These capabilities aim to transform Gmail into a proactive, AI-assisted inbox rather than just a traditional email client, with rollout starting in the U.S. and expanding over time. 

Why It Matters to Marketers: 

• AI Overviews and natural-language inbox search mean marketers and revenue teams can extract decisions and key data from lengthy email threads without manual searching, reducing time spent on administrative tasks and improving responsiveness to leads and partners.  
• Tools like Help Me Write, Suggested Replies and Proofread embed AI into everyday communications, prompting teams to adopt new norms for AI-assisted drafting and style calibration while maintaining brand voice in client and prospect outreach.  
• The new AI Inbox, which surfaces high-priority messages and actionable items, reshapes how marketers manage their daily workloads, making triage based on strategic importance easier while also requiring governance of what “priority” means for business-critical communications.  
• As Gmail scans and synthesizes email content, B2B teams must align internal policies on AI features and privacy with customer and partner data handling standards, balancing productivity gains with compliance and trust concerns. 

Google’s Gemini to Power Apple’s AI Features Like Siri 

Author: Rebecca Bellan 

Website: TechCrunch 

Just the Facts: Apple and Google have entered a multi-year partnership under which Google’s Gemini AI models and cloud infrastructure will power future Apple Intelligence features, including a major overhaul of Siri set to launch later in 2026. This marks a significant move away from Apple’s historically in-house AI strategy, with Gemini supplying the core large-language model capabilities that Apple determined were most capable after evaluating alternatives, including other AI providers. The deal comes amid broader industry competition and regulatory scrutiny and reflects the strategic importance of advanced generative AI for flagship consumer devices. 

Why It Matters to Marketers: 

• Apple’s decision to embed Google Gemini into Siri after experimenting with other models underscores that even elite tech brands now lean on best-in-class AI cores — signaling B2B marketers must plan for AI competencies to be expected in customer experiences, not optional differentiators.  
• A more capable Siri powered by Gemini will expand how users find information and take action via voice, forcing marketers to rethink measurement frameworks beyond clicks and search terms to include assistive, context-aware queries and conversions.  
• Apple’s reliance on Google’s AI models highlights the increasing importance of cross-platform alliances in shaping where and how brands engage audiences, pushing B2B leaders to evaluate integration strategies across ecosystems rather than optimizing for single platforms.  
• With Apple maintaining on-device and private-cloud processing while using a third-party model, marketing ops and RevOps teams must navigate evolving privacy expectations and data flows when activating AI-enhanced experiences without eroding trust or compromising compliance. 

How People Use AI Agents 

Author: Perplexity Team 

Website: Perplexity.ai Blog 

Just the Facts: Perplexity and Harvard researchers published the first large-scale study analyzing hundreds of millions of real-world interactions with AI agents (specifically the Comet Assistant), revealing how people actually use these tools. The research found that most agent activity isn’t limited to simple tasks like travel or trivia; instead, a majority of usage focuses on cognitive work, such as productivity, workflow, learning, and research tasks. It also showed usage evolves over time — users start with simple queries and quickly shift to complex, work-related tasks, with professionals in fields like marketing, sales and management showing particularly high engagement and intensity. 

Why It Matters to Marketers: 

• More than half of agent interactions focus on productivity and research work, signaling that B2B teams will increasingly treat AI as an extension of human analysis and decision-making rather than just a task automator — prompting updates to workflows and quality control around AI contributions.  
• Users quickly move from light queries to deep productivity tasks, showing that AI agents stick when they materially improve work output; B2B leaders should prioritize integrating agents into high-leverage workflows (e.g., market research, competitive analysis) to drive adoption and ROI.  
• Knowledge-intensive roles such as marketing, sales and management show higher sustained engagement, indicating that skill development in prompt strategy and agent supervision will become a core competency for go-to-market teams.  
• Evidence that people rely on agents as “thinking partners” suggests a structural shift toward hybrid teams in which humans and AI co-produce insights and outputs, requiring new performance metrics and accountability models that reflect shared cognitive labor.