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This Week in AI in Marketing & Management (26th May)

ByAnn Stanley

Google I/O Reshapes Search, Ads and Commerce

Google’s I/O 2026 and Google Marketing Live dominated the week, with Gemini 3.5 Flash, the always-on Gemini Spark agent, a new “intelligent” search box and the launch of Universal Cart for agentic commerce all landing within days of each other. Meta’s ads MCP server entered open beta with mixed early results, while Klarna released a shopping app inside ChatGPT and Debenhams became the first UK retailer to enable AI-driven checkout on Meta. On the management side, McKinsey sized the workforce shift at 30-50% of working hours transforming within five years, HSBC‘s CEO warned of structural change in banking, and UK HR leaders signalled they are lagging global peers on AI adoption. Here is the full briefing for the week ending 25 May 2026.

Table of Contents

AI News, Tech & Tools

AI in Marketing

AI in Management

AI in E-commerce, Retail and Agentic Commerce

AI for Other Sectors and Industries

Key Takeaways

Frequently Asked Questions

Conclusion

AI News, Tech & Tools

Google launches Gemini 3.5 Flash and Gemini Spark, an always-on agent

Sources: blog.google, cnet.com, theverge.com, theverge.com, mashable.com | 19-24 May 2026

At I/O 2026, Google unveiled Gemini 3.5 Flash as the new default model behind the Gemini app and AI Mode in Search, claiming it beats Gemini 3.1 Pro on coding and agentic benchmarks while generating richer interactive web UIs. A Gemini 3.5 Pro release is slated for June. The Gemini app also received a “Neural Expressive” redesign with smoother animations and new typography.

The headline feature is Gemini Spark, an always-on agent that runs 24/7 on Google Cloud virtual machines, drafting emails, building study guides, tracking subscriptions and connecting to Workspace plus third-party apps such as Canva, OpenTable and Instacart via the Model Context Protocol. macOS local file access arrives this summer, with Chrome and an “Android Halo” UI layer to follow. Google positions Spark as its answer to OpenClaw and Anthropic-style personal agents.

Why it matters
Spark moves consumer AI from request-response to background, proactive agents that initiate work without prompting. For marketers, the implication is significant: a meaningful share of inbox, calendar and shopping touchpoints will soon be filtered or actioned by a personal agent before the human sees them. Brand messaging, transactional emails and offers all need to be machine-parseable and useful to that agent. Start auditing how your customer comms appear when summarised, re-prioritised or auto-actioned by Gemini Spark or its competitors.

Kore.ai launches Artemis agent platform to challenge Microsoft and Salesforce

Source: venturebeat.com | May 2026

Kore.ai launched Artemis, a ground-up rebuild of its Agent Platform that lets enterprises build, govern and optimise AI agents using AI itself, compressing what was months of engineering work into days. At the core sits Agent Blueprint Language (ABL), a YAML-based declarative language with its own parser, compiler and runtime supporting six built-in orchestration patterns including supervisor, delegation, handoff, fan-out, escalation and agent-to-agent federation.

Founder Raj Koneru framed the launch as “you do AI with AI”: design, build, test, deploy, manage and optimise agents all with AI assistance. The platform’s pitch is neutrality, an attempt to position against the bundled offerings from Microsoft, Salesforce, Google and ServiceNow that are all racing to become the default infrastructure for enterprise AI agents.

Why it matters
The enterprise agent platform war is now a five-way fight, and vendor lock-in is the real strategic question. ABL is a bet that enterprises want a portable, declarative way to define agents independent of any single hyperscaler. Marketing leaders evaluating agent platforms should ask how easily agents can be migrated between vendors and whether definitions are stored in open or proprietary formats. The answer will determine your switching costs three years from now.

Google’s intelligent eyewear with Gemini launches this autumn

Source: blog.google | 19 May 2026

Google revealed new Android XR eyewear partnerships with Gentle Monster and Warby Parker, with the Gemini-powered glasses launching this autumn. Features include hands-free directions, text messaging, photography and contextual AI assistance, all without taking your phone out. The platform is built with Samsung and Qualcomm.

The release positions Google directly against Meta’s Ray-Ban smart glasses and Apple’s Vision-era hardware. Google is leaning on fashion-forward partners rather than launching its own consumer brand, mirroring the EssilorLuxottica-Meta playbook.

Why it matters
If even a fraction of smartphone users shift attention to ambient eyewear, the available attention shifts again. Visual search, location-triggered offers and voice-led discovery will all become more important. Brands should start thinking about how their physical premises, product packaging and signage perform when a Gemini-powered camera is looking at them on a consumer’s behalf.

Inside Meta’s ads MCP server: what early testers are discovering

Sources: adage.com, adage.com | 18-20 May 2026

Meta’s AI Ads Connectors, an MCP server that lets outside agents such as ChatGPT or Claude manage Meta campaigns, is in open beta but rolling out slowly with limited transparency, according to Ad Age. Early testers report that the server can automate campaign creation, audience setup, creative iteration and performance reporting through natural-language prompts to external agents.

The challenges are equally instructive: testers describe inconsistent permissions, opaque error handling and a lack of clear documentation on which Meta features are exposed. Some media buyers have hit guardrails around budget changes and creative approvals, suggesting Meta is being deliberately cautious about how much control external agents can exercise.

Why it matters
MCP-based ad management is the start of a real shift away from native ad managers towards conversational, cross-platform agent workflows. The agencies that learn to prompt these connectors well will out-execute those still clicking through Ads Manager UIs. But the early-tester pain points are a warning: build a testing protocol, log every agent action and keep a human in the loop for budget and creative sign-off until guardrails mature.

AI in Marketing

Google Marketing Live: new AI Mode ad formats and AI ad explainers

Sources: marketingdive.com, socialmediatoday.com, adweek.com, seroundtable.com | 20-22 May 2026

At Google Marketing Live, Google introduced two new ad formats within AI Mode: conversational discovery ads and highlighted answers. AI Mode is also gaining Shopping ads and an “Ads Explainer” feature that uses Gemini to tell consumers why an ad was shown. Dan Taylor, Google’s VP of global ads, framed 2026 as the year the company shifts “from marketing automation to marketing intelligence.” A new AI agent will also act as an orchestration layer across Google’s marketing platforms.

Alongside the new ad units, Google unveiled an “intelligent search box” in classic Search, full rollout of seamless AI Overviews into AI Mode, agentic booking expansion, and a “preferred label” test in AI Mode results. The week also brought the now-customary ranking volatility on I/O morning and throughout, according to Search Engine Roundtable.

Why it matters
AI Mode is no longer experimental, it is becoming the default Search experience, and the ad formats inside it look and behave nothing like classic PPC. Marketers should immediately audit how their brand appears in AI Mode for top commercial queries, test the new conversational and highlighted-answer formats as they roll out, and reset expectations on click-through and attribution. Treat AI Mode as a new channel with its own KPIs, not an extension of Search.

Google says AI optimisation is just SEO, and publishes a myth-busting guide

Sources: practicalecommerce.com, seroundtable.com | 18 May 2026

Google published a new help document, “optimising your website for generative AI features on Google Search,” explicitly stating that there is no separate discipline of “AI optimisation” or “GEO,” and that core SEO best practices remain the foundation. The document includes a myth-busting section addressing common misconceptions and emphasises the importance of unique, non-commodity content.

Key points: follow standard SEO best practices, focus on E-E-A-T, ensure crawlability for Googlebot and Google-Extended, and avoid trying to game generative outputs with prompt-style content. Google also added Markdown file support to its developer docs but clarified that Markdown is not a special Search ranking signal.

Why it matters
The “GEO is the new SEO” pitch from some vendors has been bluntly rebutted by Google itself. The practical instruction is to commit further to technical SEO hygiene, structured data, unique editorial content and brand authority signals. If your agency is selling you a separate “AI optimisation” line item, ask what it actually involves beyond strong SEO. Save the budget for content quality and brand investment.

AI in Management

McKinsey predicts 30-50% of work hours will transform within five years

Source: fortune.com | Emma Burleigh | 21 May 2026

Anu Madgavkar, a partner at the McKinsey Global Institute, told the Fortune Workplace Innovation Summit that 30% to 50% of a typical professional’s working hours and activities could be transformed within the next three to five years. The remarks sit alongside fresh McKinsey research that finds today’s technology could theoretically automate 57% of US work hours, with AI agents handling 44% and robotics a further 13%. McKinsey also concludes that every job will require some skill change by 2030.

Madgavkar’s framing of “AI fluency” is deliberately broad: it is the ability to decide which tool to use, when to use it and why, rather than mastery of any specific platform. Panel speakers from Google DeepMind and Gusto agreed, with DeepMind’s Yelena Naginsky arguing that tool-specific training is “very short-lived” and the deeper skill is problem framing. McKinsey’s research also estimates that around 70% of current workforce skills will still apply to both automatable and non-automatable tasks, so the message is redesign, not redundancy.

Why it matters
For senior marketers this is the most useful sizing of the AI workforce shift to land all week. If 30-50% of working hours genuinely transforms within five years, the case for redesigning briefs, approval workflows and agency-client operating models around AI agents is no longer speculative. Build “AI fluency” expectations into role descriptions, hiring criteria and performance reviews now. Equally important, stop treating AI training as a single course or tool certification. Treat it as an ongoing capability, embedded into how every project is scoped, briefed and reviewed.

The AI layoffs narrative: real transformation or convenient scapegoat?

Source: shrm.org | May 2026

SHRM examines whether the rising tide of “AI-driven” layoff announcements reflects genuine workflow transformation or a convenient narrative for cost-cutting that was going to happen anyway. The piece argues that many companies citing AI for headcount reduction lack the agent deployments or productivity gains to justify the claim, while others are using AI as cover for delayed structural change.

The piece notes that genuine AI transformation tends to look more like role redesign than headcount reduction in the first 12-18 months, with displacement and net hiring happening simultaneously across different functions. HR leaders are urged to demand evidence-based workforce plans rather than accept “AI made us do it” framing.

Why it matters
For marketing leaders making the case to retain or grow teams, the credibility of “AI productivity” claims now matters reputationally and operationally. If you are arguing AI lets you deliver more with the same headcount, document the specific workflows, time savings and output gains. If your CFO is arguing the reverse, ask the same question. Vague AI narratives will not survive the next budget cycle.

TalentNeuron promotes product and strategy leader to CEO as AI reshapes workforce intel

Source: recruiter.co.uk | 20 May 2026

Workforce intelligence platform TalentNeuron has promoted David Wilkins, previously chief product and strategy officer, to CEO. Wilkins, who splits his time between New York and London, has held senior roles at Oracle, Taleo and HealthcareSource. The company has also appointed Florian Fleischmann as senior VP for AI and business transformation, and Stephen Prosser as senior VP of technology.

Owner Leeds Equity Partners cited a two-year transformation that expanded strategic workforce planning, proprietary data assets and heavy investment in AI, analytics and product. Wilkins said: “AI is changing what work looks like, which skills matter and how quickly companies need to adapt.”

Why it matters
Workforce intelligence is becoming a board-level concern as AI redraws skills demand quarterly rather than annually. Marketing leaders should engage with HR and people analytics teams now to map which skills are appreciating (prompt engineering, agent design, AI governance) and which are commoditising. The skills mix in your team in 18 months will be materially different. Plan for it.

HR-tech founders say workplace transformation has only just begun

Source: peoplematters.in | May 2026

HR-tech founders and senior talent leaders gathered at a recent People Matters event argued that despite three years of AI-driven HR hype, the structural transformation of work is only at the starting line. Themes raised included the redesign of management layers, AI-native onboarding, skills-based hiring and the slow death of the job description as a primary unit of work design.

Several speakers warned that organisations focused only on cost-out automation are missing the bigger opportunity: redesigning roles around human-agent teams. Productivity gains, they argued, come from rethinking who does what, not from layering tools on top of legacy processes.

Why it matters
Marketing organisations are particularly susceptible to “tool layering” rather than genuine workflow redesign. The senior leaders winning with AI right now are the ones rebuilding briefs, approval workflows and team structures around what agents can actually do. Before you buy another AI tool, ask which of your current marketing rituals would disappear if a competent agent was sitting in the meeting.

AI in E-commerce, Retail and Agentic Commerce

Google launches Universal Cart for agentic commerce

Sources: blog.google, digitalcommerce360.com, chainstoreage.com, adweek.com | 19-20 May 2026

Google unveiled Universal Cart at I/O 2026, an intelligent shopping cart that works across merchants and across Google properties including Search, Gemini, YouTube and Gmail. Built on the Universal Commerce Protocol (UCP) co-developed with Shopify, and powered by Google Wallet, the cart proactively tracks price drops, flags product incompatibilities, highlights loyalty perks and supports checkout via Google Pay in a few taps. The Shopping Graph contains over 60 billion product listings.

Launch partners include Nike, Sephora, Target, Ulta Beauty, Walmart, Wayfair, plus Shopify merchants such as Fenty and Steve Madden. The move is widely read as a direct attack on Amazon’s checkout moat, keeping consumers inside Google properties rather than clicking out to merchant sites.

Why it matters
Universal Cart is the most consequential commerce announcement of the year so far. If consumers can build multi-merchant carts inside Gemini, YouTube and Search without ever visiting a brand site, retailers lose the on-site upsell, the email capture, the recommendation slot and a big chunk of attribution clarity. Audit your UCP/MCP readiness now, work out which products you want visible in agentic baskets, and pressure-test your margin model when Google sits between you and the customer.

Klarna launches AI shopping search app inside ChatGPT

Source: digitalcommerce360.com | 20 May 2026

Klarna launched Klarna Shopping Search, an OpenAI ChatGPT app that lets consumers describe what they want and see visual results with live prices, availability and offers from multiple merchants in a single conversation. Unlike Google Universal Cart, Klarna’s app redirects shoppers to merchant sites to complete the purchase. The move follows Klarna’s recent integration with Google AI Mode for BNPL on agentic transactions.

The launch positions Klarna as a discovery and BNPL layer across both Google and OpenAI agentic platforms, a deliberate strategy of platform neutrality at a time when shoppers are starting to ask agents rather than search engines for product recommendations.

Why it matters
For retailers, the ChatGPT shopping channel is now a real acquisition route, not a curiosity. If you offer BNPL via Klarna, ensure your product feed, imagery and stock data flow correctly into Klarna’s search index. For finance and payments teams, the question is whether to bet on one BNPL partner or maintain optionality as multiple providers race to embed in agent ecosystems.

Debenhams Group becomes first UK retailer to enable AI checkout on Meta

Source: channelx.world | 21 May 2026

Debenhams Group has become the first UK retailer to enable AI-driven checkout on Meta platforms for its US customers. The integration allows shoppers to complete purchases directly within Meta’s properties using AI-assisted flows, reducing drop-off between discovery on Instagram or Facebook and conversion.

The launch is initially limited to US customers but provides a clear template for UK retailers exploring agentic commerce on social platforms. It also signals Meta’s continued push, alongside its ads MCP server, to make its properties endpoints for completed transactions rather than just discovery.

Why it matters
UK retailers should watch Debenhams’ performance closely. If AI-driven Meta checkout meaningfully improves conversion, the case for re-platforming UK social commerce will sharpen quickly. Even if you are not ready to integrate, model the impact: what happens to your social ROAS, attribution and email capture rate if 30% of social-originated sales never touch your site?

In agentic commerce, your brand promise must be provable

Source: martech.org | Greg Kihlstrom | 22 May 2026

MarTech argues that as nearly 70% of consumers and 73% of B2B buyers now use AI tools to evaluate purchases, brand value is shifting from a perception advantage to a verifiable advantage. Bain forecasts agentic AI will drive 25% of US ecommerce, or $300-500 billion, by 2030. AI agents evaluate price transparency, fulfilment reliability, reviews, loyalty value, privacy practices and service history, not brand sentiment.

The author’s argument: consumers may still pick brands emotionally, but their agents will scrutinise the brand using measurable signals. Brands need to be both machine-readable for agents and emotionally resonant for humans.

Why it matters
This is the strategic frame senior marketers should adopt for the next 12 months. Run an honest audit: can a third-party agent easily verify your delivery promises, return policy, loyalty redemption rates and review authenticity? If not, you have a brand-readability gap that will cost you share as agent-mediated discovery scales. Structured data, reliable APIs and provable service KPIs are now brand investments.

AI for Other Sectors and Industries

FINANCE: HSBC CEO Georges Elhedery warns AI will reshape banking jobs

Source: fintechmagazine.com | Maya Derrick | 24 May 2026

HSBC CEO Georges Elhedery publicly warned that AI will substantially reshape banking roles, with implications across operations, compliance, customer service and middle-management functions. The comments add HSBC’s voice to a growing list of major bank CEOs framing AI as a structural workforce shift rather than a productivity tweak.

Banking has been one of the fastest sectors to deploy generative AI internally, from copilots for relationship managers to AI-assisted compliance reviews. Elhedery’s framing suggests HSBC expects net role reduction in some areas alongside hiring in AI engineering, data and governance.

Why it matters
Financial services marketers should expect their internal stakeholders (compliance, product, legal) to be reorganised over the next 12-24 months. Approval cycles, brand governance and product launch processes will all shift. Build relationships with the emerging AI governance functions inside banking clients now, they will own decisions that previously sat with marketing and product alone.

HEALTHCARE: Significant gap between AI expectations and scaled adoption

Source: consultancy-me.com | 19 May 2026

A Riverbed study finds 91% of healthcare leaders say AI ROI has met or exceeded expectations, but only 31% describe themselves as fully ready to operationalise AI strategies. 88% agree data quality is critical to AI success, yet only around half are confident in their data. Global AI spend nearly doubled from $14.7m in 2024 to $27m in 2025, with 78% of respondents reporting increased AI investment.

The gap is structural: pilots produce strong returns, but scaling requires data infrastructure, governance and clinical workflow redesign that most organisations have not completed.

Why it matters
Healthcare marketers and life sciences agencies should expect protracted procurement cycles on AI-enabled products. The buying group is expanding to include CDOs and clinical informatics leads who will probe data quality and integration first. Lead with evidence of clean data flows, interoperability and governance, not just clinical outcomes.

HEALTHCARE: Why healthcare private equity is racing into AI

Source: themiddlemarket.com | Paul Elias | 22 May 2026

Mergers & Acquisitions reports that healthcare-focused private equity firms are accelerating AI-related investments, both in pure-play AI healthcare companies and in adding AI capability to existing portfolio assets. Drivers include staffing shortages, reimbursement pressure and the maturation of clinically validated AI tools across imaging, scheduling and revenue cycle management.

The trend is reshaping deal valuation models: PE firms are increasingly asking whether a target’s revenue is defensible against AI-enabled competitors, and whether AI can be deployed quickly enough post-acquisition to drive margin expansion within a typical hold period.

Why it matters
For agencies and martech vendors serving healthcare, the buyer universe is shifting under PE pressure. Expect compressed decision cycles, harder ROI demands and consolidation across portfolio companies. Healthcare CMOs working inside PE-backed assets should expect AI mandates from the board within the next 12 months.

HR: UK lags global peers on AI-driven hiring growth in 2026

Source: thehrdirector.com | 21 May 2026

A YouGov survey for HireRight finds UK HR leaders significantly more cautious about AI than global peers. Globally, a net +13% expect AI-driven workforce growth in 2026, but in the UK just 18% expect AI to increase hiring volumes versus 52% in India and 43% in Brazil. 42% of UK HR leaders are not currently using AI in HR, the highest of any market surveyed. Only 12% of UK HR leaders are “very confident” they can detect candidates using GenAI in applications, versus 54% in India.

Training and development (25%) and candidate selection (25%) are the most common UK AI use cases, but adoption sits well below the global averages of 40% and 32% respectively.

Why it matters
UK marketing leaders should treat this as a competitive warning. If UK HR functions are slower to adopt AI, your talent acquisition cycles, candidate quality and skills-mapping will lag faster-moving markets. Push HR partners to pilot AI-assisted sourcing and skills inference, and build internal AI fluency into job descriptions now. The teams that hire for AI-native skills in 2026 will outperform those still writing 2023-era role specs.

HEALTHCARE: IBM, Fujitsu, SMBC and SoftBank partner on AI-driven healthcare in Japan

Source: healthcare-digital.com | Lucy Potter | 23 May 2026

Japan’s healthcare sector is undergoing rapid digital transformation as IBM Japan, Fujitsu, Sumitomo Mitsui Financial Group and SoftBank collaborate to build secure, AI-driven healthcare ecosystems. The initiatives focus on data sovereignty, interoperability across institutions and AI-enabled patient care. Tesco also published its 2026 Sustainability Report covering pharmacy services and early detection, while KPMG released research on climate-resilient healthcare in the Bahamas.

The Japanese consortium model, with banks and telcos sitting alongside cloud and AI providers, is a useful template for how regulated sectors can pool infrastructure, data governance and capital to deploy AI at national scale.

Why it matters
Cross-sector consortia are increasingly the structure through which AI scales in regulated industries. Marketers in healthcare, finance and public sector should expect consortium-led RFPs rather than single-buyer procurements. Position your propositions to fit multi-stakeholder governance and data-sovereignty requirements from the outset.

Key Takeaways

  • Google’s Universal Cart, powered by UCP and Google Wallet, launches with Nike, Sephora, Target, Ulta, Walmart, Wayfair and Shopify partners, putting agentic checkout directly inside Search, Gemini, YouTube and Gmail.
  • Gemini 3.5 Flash is now powering AI Mode and the Gemini app, with Gemini Spark running 24/7 as an always-on personal agent connected to Workspace and third-party apps via MCP.
  • McKinsey sizes the AI workforce shift at 30-50% of working hours transforming within three to five years, and concludes every job will require some skill change by 2030. Treat AI fluency as a permanent capability, not a one-off training course.
  • Google has publicly stated that “AI optimisation” is just SEO, and published a myth-busting guide. Reallocate budget from speculative GEO consultancy to content quality and brand authority.
  • Meta’s ads MCP server is in open beta with significant pain points around permissions, error handling and creative approvals. Test with strict logging and human-in-the-loop controls.
  • Klarna launched a shopping search app inside ChatGPT, and Debenhams became the first UK retailer to enable AI checkout on Meta for US customers. Social and chatbot channels are now real conversion routes.
  • HSBC’s CEO publicly framed AI as a structural workforce shift in banking. UK HR is notably behind India, Brazil and Australia on AI adoption, with 42% of UK HR teams not yet using AI at all.
  • Bain forecasts agentic AI will drive 25% of US ecommerce ($300-500bn) by 2030. Brand promises must be machine-verifiable, not just emotionally resonant.

Frequently Asked Questions

How should we prepare for Universal Cart and agentic commerce?

The starting point is an audit of your product feed quality, structured data and API readiness for the Universal Commerce Protocol (UCP) and the Model Context Protocol (MCP). If you are on Shopify or Magento, both platforms already have first-party and partner plugins that handle the bulk of feed structure, MCP exposure and Universal Cart compatibility, so the practical job is configuring and validating those plugins rather than building anything from scratch.

For brands on bespoke or older platforms, or for anyone who wants an independent view of how their data appears to agents, the Anicca team runs a dedicated agentic-commerce readiness audit. It covers feed coverage, structured data, identity and authentication signals, plus the margin model when Google or another agent intermediates the basket. Get in touch if you would like us to run this for your brand.

Is “AI optimisation” or GEO a real thing we should pay for?

Google’s own guidance is that there is no separate discipline of AI optimisation, and that strong SEO fundamentals (structured data, E-E-A-T, unique non-commodity content) are the foundation for visibility in AI Overviews and AI Mode. The Anicca view is that this is correct as far as it goes, but it is not the whole picture. SEO and GEO need to be tackled together as one integrated service, because the underlying work is shared, while the content, citations and authority signals that win in classic Search are not always the same as the ones that earn citations inside Gemini, ChatGPT, Perplexity and AI Mode.

What we recommend is an integrated SEO and GEO programme with the two reported on separately so you can see where the effort is paying back. That means doing the technical SEO and content hygiene work once, then adding the GEO-specific work of citation building, brand-mention monitoring, structured FAQs and authoritative content that agents will quote back. Be sceptical of any agency selling a standalone GEO line item that is just rebadged link-building. Talk to the Anicca team if you would like a combined audit of where you sit today on both fronts.

Should we trust Meta’s ads MCP server for live campaigns yet?

Use it for testing, automation of repetitive setup tasks and reporting, but keep humans in the loop for budget changes and creative approvals. Early testers report inconsistent permissions and limited transparency, so log every agent action and start with low-spend campaigns until guardrails mature.

Conclusion

This was the week agentic commerce stopped being a thought experiment. Between Google’s Universal Cart, Klarna inside ChatGPT, Debenhams on Meta and Gemini Spark running personal agents 24/7, the buyer journey is being intermediated by software at every stage. Three actions for senior marketers this quarter: first, audit your machine-readability across product data, brand claims and service KPIs, agents will judge you on these. Second, treat AI Mode and agent platforms as new channels with distinct KPIs, not extensions of Search. Third, stress-test your team structure and skills mix against an AI-driven workforce shift that is now being signalled by CEOs in banking, healthcare and beyond.

Need help adapting your AI marketing strategy? Contact the Anicca team for expert guidance.

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This roundup is compiled from publicly available sources using AI-assisted research. While we review every article for accuracy, our analysis reflects our interpretation of the original reporting. We strongly encourage readers to click through to the original sources linked throughout this post for full context and detail. If you spot anything that needs correcting, please let us know.

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