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Dull for customers, that is. Across industries, businesses are finding ways to implement generative AI. They're looking for operational efficiencies, ways to automate tasks, and ways to scale impact. Many see customer-focused roles as a natural fit. They're reinventing the face of the business, using generative AI for customer service or ad material generation and integrating chatbot interfaces into products. But if they're not careful, every business is about to wind up with the same face. Effectively, enterprises are imbuing the customer experience with autonomy. Agents, bots, and technology systems can drive sales, solve problems, set meetings and do much more for customers. But the foundation models driving many of these experiences are built by the same few organizations and are designed—intentionally—to be as neutral-sounding as possible. It's a simple insight, perhaps inconsequential at first glance. But enterprises are creating the customer interface that will define their next decade—and how they design it has profound, far-reaching implications. Businesses are teetering on the edge of a customer engagement crisis. It's one that started growing during the digital era. When new digital channels started emerging, and customer touchpoints shifted to platforms and search engines, businesses could connect to more customers than ever, but direct conversation with them became muted, and differentiation became more challenging. Now, in the AI era, this engagement crisis is at risk of being compounded. AI models and the growing autonomy of digital systems can generate massive opportunity, the chance to have one-on-one conversations at unprecedented scale. But if these models are fine-tuned for function, and not experience, they'll sound generic or bland and leave all that potential unrealized. This won't just be a problem on the enterprises' channels either. Looking towards the future, it becomes even sharper as generative AI-based chat platforms position themselves as the primary window to the digital world. When a third-party agent invites your companies' agents into a conversation with a customer, what will it sound like? 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Nomi AI is creating AI companions that people can text in group chats or one-on-one. 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In April 2024, Instagram began testing Creator.ai, which provides a program that will let influencers connect with fans through chatbots that mimic their voices.", "attrs": null, "canon": { "kind": { "name": "Paragraph", "slug": "paragraph", "status": "active", "canonId": "5f2affc0-941d-4d07-959d-4bfc1930cea4", "version": 1, "description": "Single prose block in the body of a slide." }, "tool": null, "subkind": { "name": "Paragraph", "slug": "paragraph", "status": "active", "canonId": "019de52c-fb80-75af-aa5c-a7a4bfac2433", "version": 1, "description": null }, "framework": null }, "subkind": "paragraph", "groupRole": null, "confidence": null, "extraction": { "at": "2026-05-02 18:08:33.075+00", "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "seconds": null, "promptVersion": null }, "componentId": "0e033aff-3c9a-4ac3-a0d1-d607c93e767c", "parentComponentId": null }, { "bbox": { "h": 0.15, "w": 0.28, "x": 0.66, "y": 0.08 }, "kind": "paragraph", "text": "Enterprise leaders know people are capable of building powerful—and valuable—attachments to brands with strong personalities. 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While leaders hunt for the value machine-like consistency can bring, they need to ensure they don't overshadow the very things that create enriching and personal human experiences.", "attrs": null, "canon": { "kind": { "name": "Paragraph", "slug": "paragraph", "status": "active", "canonId": "5f2affc0-941d-4d07-959d-4bfc1930cea4", "version": 1, "description": "Single prose block in the body of a slide." }, "tool": null, "subkind": { "name": "Paragraph", "slug": "paragraph", "status": "active", "canonId": "019de52c-fb80-75af-aa5c-a7a4bfac2433", "version": 1, "description": null }, "framework": null }, "subkind": "paragraph", "groupRole": null, "confidence": null, "extraction": { "at": "2026-05-02 18:08:33.075+00", "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "seconds": null, "promptVersion": null }, "componentId": "8c8fd701-b81e-42bd-a1d2-dc251bed5573", "parentComponentId": null }, { "bbox": { "h": 0.2, "w": 0.28, "x": 0.35, "y": 0.65 }, "kind": "paragraph", "text": "What we know is this: Businesses have long depended on the power of brand personality. 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Autonomous systems and AI personification have incredible potential to transform customer relationships, building one-on-one rapport and loyalty, reshaping how customers' needs are met, and giving customers the kind of individualized attention that digital businesses have never been able to deliver at scale. But all of it depends on trust. To get to know people well enough to meet their needs and take productive, relevant actions on their behalf, people need to be willing to open up. What good is a personified agent if customers are too afraid to talk to it? 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It's no small task given people's general concern about sharing data and, among some, skepticism around AI. But the potential of personified business is too big to miss—it could launch a new era of autonomy in customer relationships and reshape entire value chains. 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It consistently ranks as one of the chief concerns people and enterprises alike have with AI. Fortunately, some solutions to achieve the personalization AI promises, without compromising security and privacy, are already at play. Synthetic data can be an option to keep PII away from models. Where private data is required, some techniques include ensuring conversations are deleted or that functions are restricted to remain on devices. For instance, to preserve customer privacy in its copilot Recall feature, Microsoft makes sure all screenshots are stored and processed locally. There's no one-size-fits-all, but security must be top of mind as businesses introduce greater autonomy to customer-facing features. 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If a customer wants to know why they are receiving a particular recommendation, they'll need to be able to probe the chatbot. What's more, hallucinations continue to be a part of the generative AI experience, so if a user is not achieving an expected outcome, explainability can help them identify where mistakes have been made—and escalate to a human if needed. 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It means every interaction with AI is not just building or breaking customers' trust with the enterprise, but with the technology itself. And it means the rollout of autonomous systems and the personified business needs to be in lockstep with customers—directed first by where they trust and benefit from this technology, only progressing as their trust grows.", "attrs": null, "canon": { "kind": { "name": "Paragraph", "slug": "paragraph", "status": "active", "canonId": "5f2affc0-941d-4d07-959d-4bfc1930cea4", "version": 1, "description": "Single prose block in the body of a slide." }, "tool": null, "subkind": { "name": "Paragraph", "slug": "paragraph", "status": "active", "canonId": "019de52c-fb80-75af-aa5c-a7a4bfac2433", "version": 1, "description": null }, "framework": null }, "subkind": "paragraph", "groupRole": null, "confidence": null, "extraction": { "at": "2026-05-02 18:08:35.389+00", "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "seconds": null, "promptVersion": null }, "componentId": "bfcc1368-2778-4099-b9a6-57ddcd47459a", "parentComponentId": null }, { "bbox": { "h": 0.25, "w": 0.21, "x": 0.275, "y": 0.48 }, "kind": "paragraph", "text": "Starting with awareness might seem strange. Most business leaders are used to leveraging technology already in people's hands, not needing to advocate for it. But generative AI is putting enterprises in a unique—slightly awkward—position. Consider this: the Michigan State University Federal Credit Union (MSUFCU) developed a chatbot named Fran, and in a survey of some of MSUFCU's low- and medium-income families, 44% said they felt nervous about using AI technology, but of that percentage, 70% said they liked using Fran.", "attrs": null, "canon": { "kind": { "name": "Paragraph", "slug": "paragraph", "status": "active", "canonId": "5f2affc0-941d-4d07-959d-4bfc1930cea4", "version": 1, "description": "Single prose block in the body of a slide." }, "tool": null, "subkind": { "name": "Paragraph", "slug": "paragraph", "status": "active", "canonId": "019de52c-fb80-75af-aa5c-a7a4bfac2433", "version": 1, "description": null }, "framework": null }, "subkind": "paragraph", "groupRole": null, "confidence": null, "extraction": { "at": "2026-05-02 18:08:35.389+00", "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "seconds": null, "promptVersion": null }, "componentId": "dd732bca-7c0f-4ce0-bf52-0686c2ac6f2d", "parentComponentId": null }, { "bbox": { "h": 0.4, "w": 0.21, "x": 0.04, "y": 0.18 }, "kind": "quote", "text": "...every interaction with AI is not just building or breaking customers' trust with the enterprise, but with the technology itself.", "attrs": null, "canon": { "kind": { "name": "Quote", "slug": "quote", "status": "active", "canonId": "019de52c-f8fb-751e-8bc6-d58e2d59562a", "version": 1, "description": "Pull quote or testimonial." }, "tool": null, "subkind": { "name": "Pull quote", "slug": "pull-quote", "status": "active", "canonId": "019de52c-fbf9-76fe-97e1-a0b7540445c9", "version": 1, "description": null }, "framework": null }, "subkind": "pull-quote", "groupRole": null, "confidence": null, "extraction": { "at": "2026-05-02 18:08:35.389+00", "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "seconds": null, "promptVersion": null }, "componentId": "576848fe-7d29-4962-879c-5ffa70f228d9", "parentComponentId": null }, { "bbox": { "h": 0.03, "w": 0.15, "x": 0.275, "y": 0.1 }, "kind": "title", "text": "The Implications", "attrs": null, "canon": { "kind": { "name": "Title", "slug": "title", "status": "active", "canonId": "019de52c-f7dd-76d9-b848-b1f12bd85cf4", "version": 1, "description": "Slide title or headline." }, "tool": null, "subkind": { "name": "Headline", "slug": "headline", "status": "active", "canonId": "019de52c-fae1-7463-9a7c-d60668eced0d", "version": 1, "description": null }, "framework": null }, "subkind": "headline", "groupRole": null, "confidence": null, "extraction": { "at": "2026-05-02 18:08:35.389+00", "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "seconds": null, "promptVersion": null }, "componentId": "f8a47872-f66b-45c5-8a5a-e07f5384bff5", "parentComponentId": null } ], "metrics": [], "tools": [ { "tool": { "name": "Action Titles", "slug": "action-titles", "status": "active", "bestFor": "Any decision-grade deliverable — strategy recommendation, board update, investment memo, M&A review, post-mortem — where the reader is being asked to agree, decide, or act and will skim the title bar at speed.", "canonId": "019dd956-ac70-700b-a608-ba58e78f5dcc", "version": 1, "bodyDocId": "816dad3c-9983-41c1-a86e-978ebd582841", "description": "The McKinsey-bred discipline of writing every slide title as a complete declarative sentence with a verb and an insight, not a topic label. 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Trust will also be critical to true real-world viability. People won't just need to work with the machines around them, but trust and depend on them as well. Enterprises looking to spur their robotics revolution will have to consider new dimensions of the human-machine relationship. Like, what happens when responsible AI practices migrate into the physical world? What decisions will a machine make when faced with an emergency or impending accident? What will it mean to steward a new generation of physical (and possibly energy intensive) technology in a sustainability-conscious landscape? 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Extremely low power consumption will be a core competency to allow them to run with the duration and efficiency needed to tackle tasks they will be given. Latency will also be key: waiting 30 seconds for a machine to respond to a request will break the real-world immersion, so understanding how robots will handle requests, not just with human-like capability but at human-like speed, will require decisions about where models are hosted and how robots are networked. Finally, as foundation models deepen into other areas of science, like physics and chemistry, adapting these models to give robots an even deeper contextual understanding of our physical environments will be the next big step forward.", "attrs": null, "canon": { "kind": { "name": "Paragraph", "slug": "paragraph", "status": "active", "canonId": "5f2affc0-941d-4d07-959d-4bfc1930cea4", "version": 1, "description": "Single prose block in the body of a slide." }, "tool": null, "subkind": { "name": "Paragraph", "slug": "paragraph", "status": "active", "canonId": "019de52c-fb80-75af-aa5c-a7a4bfac2433", "version": 1, "description": null }, "framework": null }, "subkind": "paragraph", "groupRole": null, "confidence": null, "extraction": { "at": "2026-05-02 18:08:35.685+00", "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "seconds": null, "promptVersion": null }, "componentId": "94170905-9c84-4506-b6cb-fe5cf0557d58", "parentComponentId": null }, { "bbox": { "h": 0.25, "w": 0.28, "x": 0.045, "y": 0.085 }, "kind": "paragraph", "text": "robot deployments. Unlike in the past, these robots can handle changing environments, complex and unpredictable work, and can learn new capabilities and be redeployed. This means companies can be more experimental with them, trial running new use cases, A/B testing different customer-facing deployments, and revising as needed. 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null }, "componentId": "044ba027-a728-4277-8bdd-262d07957d99", "parentComponentId": null }, { "bbox": null, "kind": "metric", "text": "Executive expectation for Gen AI accessibility: 49%", "attrs": null, "canon": { "kind": { "name": "Metric", "slug": "metric", "status": "active", "canonId": "019de52c-f923-73bf-8081-d0b1a8c5264d", "version": 1, "description": "Big-number or KPI value." }, "tool": { "name": "Quantification", "slug": "quantification", "status": "active", "bestFor": null, "canonId": "019dd9e1-47ab-72ce-a079-aab1f5299e88", "version": 1, "bodyDocId": null, "description": "Translating a claim into numbers, charts, or tables.", "familyLabel": null }, "subkind": null, "framework": null }, "subkind": "primary", "groupRole": null, "confidence": null, "extraction": { "at": "2026-04-24 14:56:32+00", "model": "or:google/gemini-3.1-flash-lite-preview", "runId": null, "seconds": null, "promptVersion": null }, "componentId": "019dd952-0a6b-775b-a1de-e2a221b32d7a", "parentComponentId": null }, { "bbox": { "h": 0.2, "w": 0.4, "x": 0.05, "y": 0.5 }, "kind": "paragraph", "text": "Camunda, a workflow automation provider, is adding AI capabilities to its platform. 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