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Capgemini unveils strategic AI framework to turn enterprise

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Mollie Mellows
Phone:+ 44 (0) 7342 709384
E-mail: mollie.mellows@capgemini.com

Capgemini unveils strategic AI framework to turn enterprise ambition into measurable business impact

Paris, July 3, 2025 – Capgemini today unveiled its Resonance AI Framework to help organizations unlock the full potential of AI at scale, reimagining their business from operations to innovation. With the vast majority of organizations planning to implement agentic AI in the next 2 years1, there is a strong need to reinforce organizations’ AI readiness, while creating the right “human-AI chemistry” to ensure long-lasting adoption. Supported by a suite of AI transformation offers and RAISE, a comprehensive generative AI and AI agents gallery, the framework enables organizations to turn strategy into action across the enterprise.

In an era of unprecedented transformation, AI can release waves of opportunities across industries, ranging from performance improvement to breakthrough innovation and business reinvention. The Resonance AI Framework by Capgemini helps leaders envision AI’s potential, embed it into the foundation of their operations, and enable what Capgemini terms “human-AI chemistry”. Designed to allow effective interaction between people and intelligent systems, the framework addresses the trust, understanding, and collaboration needed for human and AI agents to build reliability over time, ensuring that hybrid teams thrive.

The Resonance AI Framework combines the breadth of the Group’s capabilities, enabling seamless delivery of cohesive, responsible, and high-impact solutions to clients. It is a strategic blueprint that helps organizations navigate a new world of democratized AI, release the next waves of human-AI innovation, and secure long-term adoption.

“At Capgemini, we believe AI is becoming the next utility – accessible everywhere, anytime, and by anyone. This democratization of AI empowers businesses to embed AI into the fabric of everyday operations,” said Aiman Ezzat, Chief Executive Officer of the Capgemini Group. “At the heart of the framework is the concept of resonance, the idea that AI transformation must begin at the core of an organization and radiate outward to generate continuous waves of value. Our approach offers a clear path forward: one that aligns vision with execution, strategy with operations, and innovation with responsibility. This is how the next market-leading businesses will thrive, by fostering human-AI interaction and making AI performance real.”

Releasing the next waves of human-AI innovation
To deliver business value, the Resonance AI Framework by Capgemini equips organizations to act across three strategic dimensions:

  • AI essentials (ACCESS): The core components required to unlock actionable intelligence and transformative value within an organization. It is the combination of two critical components: Intelligent-as-a-Service, which includes scalable infrastructure, advanced language models, and software with built-in AI capabilities; and the organization’s raw data – unique, unprocessed, and often underused assets that power meaningful insights.
  • AI readiness (ADAPT): This is about preparing the organization to use AI responsibly and effectively. It involves establishing the right enablers, such as workforce models, governance frameworks, and data infrastructure. The implementation of guardrails is also required to ensure ethical, legal, and safe AI operations. Together, these foundations support scalable adoption.
  • Human-AI chemistry (ADOPT): To achieve success with AI, organizations must intentionally design interactions between humans and AI across workflows, decision-making, and culture. The quality of collaboration between humans and AI is shaped by three core elements: clearly defined roles and responsibilities, well-designed interactions, and strong alignment with legal and ethical standards to build reliability over time. Just as team chemistry drives human performance, human-AI chemistry will shape how deeply AI can integrate into the enterprise.

A comprehensive AI-first portfolio of offers delivering client outcomes
Capgemini’s framework is supported by a broad suite of transformation offers, each designed to help organizations derive tangible value from AI. These include:

  • Envisioning and building the AI strategy roadmap
  • Developing AI-powered experiences, products and innovation
  • Boosting AI-powered go-to-market
  • Uplifting business outcomes with AI-powered business process operations
  • Evolving faster with AI-powered IT

These offers are supported by a comprehensive and enterprise-ready generative AI and AI agents builder and gallery that will be constantly evolving to support new market opportunities (RAISE).

Already being adopted by clients worldwide, the framework is poised to become a global standard for enterprise AI transformation. From manufacturing to financial services, organizations are using it to craft their AI roadmaps, hyper-automate business process and IT operations, and reimagine customer engagement.

For example, Capgemini is working with a global pharmaceutical leader to address slow resolution times, high support costs, and low user satisfaction in its IT service desk. By introducing agentic and generative AI, the organization reduced average handling time by 20%, improved first contact resolution and user satisfaction, enabled up to 80% zero-touch automation, and cut operational costs by 40%.
  
The business and technology transformation partner enabling AI-powered enterprises
The launch of the Resonance AI Framework is the latest initiative from Capgemini to strengthen its leadership in AI. Over the last two years, Capgemini has accelerated its AI strategy by upskilling over 150,000 team members on generative AI tools and establishing AI Centers of Excellence plus two AI-focused Labs (AI Futures and AI Robotics & Experiences). With a broad ecosystem of 25 strategic partners in AI, the Group has invested in strengthening its partnerships with key players across the AI value chain, including AWS, Google Cloud, Microsoft and Mistral AI. Capgemini’s leadership in AI has also been recognized by the Forrester Wave™: AI services, Q2 2024.

Organizations can learn more about the Resonance AI Framework by Capgemini and how it can help them lead in the age of intelligence here.

About Capgemini
Capgemini is a global business and technology transformation partner, helping organizations to accelerate their dual transition to a digital and sustainable world, while creating tangible impact for enterprises and society. It is a responsible and diverse group of 340,000 team members in more than 50 countries. With its strong over 55-year heritage, Capgemini is trusted by its clients to unlock the value of technology to address the entire breadth of their business needs. It delivers end-to-end services and solutions leveraging strengths from strategy and design to engineering, all fueled by its market leading capabilities in AI, generative AI, cloud and data, combined with its deep industry expertise and partner ecosystem. The Group reported 2024 global revenues of €22.1 billion.

Get The Future You Want | www.capgemini.com

1 “Top Tech Trends of 2025: AI-powered everything”, Capgemini Research Institute, November 2024



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Imperfect AI creates more editing business opportunities – DIGITIMES Asia

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September 6, 2025

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Imperfect AI creates more editing business opportunities  DIGITIMES Asia



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OpenAI forecasts $115 billion business spend on AI rollout by 2029

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September 6, 2025

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OpenAI has elevated its cash burn forecast this year through 2029 to a total of $115 billion. The company’s recent cash burn expectation is also $80 billion higher than it previously projected. 

According to a report by The Information, the surge in cash burn for OpenAI comes at a time when it’s ramping up spending to power the artificial intelligence behind its popular ChatGPT chatbot. The tech firm has also become one of the world’s biggest renters of cloud services.

OpenAI plans to develop its chips and data center facilities

The source revealed that the AI company expects to burn over $8 billion this year. OpenAI had forecasted early in the year that it would only burn around $1.5 billion.

According to the report, OpenAI doubled its cash burn expectations for 2026 to more than $17 billion, surpassing its previous forecast of $10 billion. The firm also projects a $35 billion cash burn in 2027 and $45 billion in 2028. 

The FT also disclosed on Thursday that the Silicon Valley startup plans to develop its data center server chips and facilities to power its technology. According to the report, the initiative aims to control the tech company’s surging operational costs.

The firm relies on substantial computing power to train and run its systems. The company’s CEO, Sam Altman, has also advocated the need for increased computing power to accommodate the growing demand for AI products such as ChatGPT.

Deloitte’s 2025 AI infrastructure Survey revealed that the energy demands of AI are straining traditional power grids. According to the study, 79% of executives anticipate increased power demand through the next decade, with grid stress emerging as a top challenge.

The source added that U.S. semiconductor giant Broadcom will partner with OpenAI to produce the first set of chips and start shipping them by next year. Also, OpenAI allegedly plans to use the chips internally rather than selling them for external clients. 

Broadcom’s CEO, Hock Tan, hinted the company had partnered with an undisclosed customer that committed to $10 billion in orders. During a call with analysts, he revealed the firm had secured a fourth customer to boost its custom AI chip division. Tan stated the collaboration with OpenAI has enhanced its growth outlook for fiscal 2026 by generating immediate and substantial demand. 

OpenAI partners with Broadcom to produce chips

OpenAI also partnered with Broadcom and Taiwan Semiconductor Manufacturing Co. (TSMC) nearly a year ago to develop its first in-house chip. The firm was also planning to add AMD chips alongside Nvidia chips to meet its surging infrastructure demands.

OpenAI revealed in February plans to reduce its reliance on Nvidia’s chips. The firm said it will finalize the design of the new chip in the next few months and then send it to TSMC for fabrication. OpenAI’s initiative also builds on its ambitious plans to increase its semiconductor production at the Taiwanese company next year.

According to the report, OpenAI hopes to use the new chips to strengthen its negotiating leverage with other chip suppliers, including Nvidia. The company’s in-house team, led by Richard Ho, will design the chip to produce advanced processors with broader capabilities with each new iteration.

OpenAI collaborated with Oracle in July to launch a 4.5-gigawatt data center. The initiative also complements the firm’s $500 billion Stargate project, including investments from Japanese firm SoftBank Group. The tech giant has also collaborated with Google Cloud to supply computing capacity.

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Need to Rank in AI Overviews? These SEO Agency Specializes in them

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September 6, 2025

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Search is changing. AI-generated answers now appear in nearly half of all queries, creating new conditions for brand visibility. This affects how people find and trust brands online. Agencies with a narrow focus and unique capabilities have stepped in to meet this need. Among them, Growing Search manages both classical and AI-driven search with all work in-house. Their approach uses internal tools to track, analyze, and improve citations and sentiment across search platforms powered by artificial intelligence, such as ChatGPT and Perplexity. This article examines the tactics, technology, and reported impact of Growing Search in the context of this new search environment.

 

AI Overviews: A New Standard for Brand Visibility

Recent data shows that AI-generated summaries now appear in over 42% of all search results as of 2025. These AI Overviews usually display above regular listings and paid ads. The impact is straightforward. When a brand appears in these boxes, it commands user attention at the first step of a search. The positioning affects both user awareness and perceived authority.

Users often interact with AI-generated content before considering the rest of the results page. As a result, the context and credibility of source content have become essential. Brands must be discoverable and present information in a way that artificial intelligence can interpret as both trustworthy and relevant.

Unique Challenges in AI Search

AI search systems, including those behind Gemini, ChatGPT, and Perplexity, work differently from traditional engines. They scan many sources but look for signals beyond repeating keywords. They prefer content that is context-aware, semantically precise, and written by authorities in the subject. This approach changes what is needed to earn citations.

Old methods, which relied heavily on repeating high-traffic keywords, now hold less value. Instead, there are new requirements:

  •     Content must match the detailed intent of the user’s query, not only broad or superficial keyword strings.
  •         The writing must signal expertise and context that AI can detect and validate.
  •     Brand mentions and topic clusters, called entities, must be visible and consistent to help artificial intelligence select credible sources.

Citations in AI answers have grown more valuable. When users see these automated answers, the sources cited enjoy increased trust, even if most people do not click through to the original page. This influence shapes user decisions and can drive tangible results, such as more inquiries or conversions.

How Growing Search Approaches AI-Driven SEO

Growing Search focuses on both established and AI-powered search platforms. They manage audits, keyword research, content structuring, and link building. Their added strength is tracking brand mentions and sentiment within artificial intelligence tools, not only on classic search engines.

With everything handled in-house, the agency ensures accuracy and keeps processes efficient. They do not depend on third parties to handle data or make changes. This direct control is reported to result in faster responses and stronger data privacy.

Proprietary Tools: StakeView and BrandLens

Growing Search’s approach centers on two internal analytics platforms: StakeView and BrandLens.

StakeView gives brands ongoing analysis of their organic market share against competitors. It shows results for both standard search engines and AI answer engines. This lets clients see shifts in their presence and make quick decisions if needed.

BrandLens tracks sentiment and citation occurrences for a brand in AI-powered platforms. The software measures both the volume of mentions and the tone. It shows whether a brand is being named as an authority, described in a neutral voice, or mentioned with negative intent. This feedback is vital because search engines and users both react to subtle shifts in brand reputation triggered by AI answer summaries.

Industry commentary points to this kind of tracking as a necessity. As AI Overviews become more common, exposure in these features offers advantages even for those not at the top of traditional ranking pages. If a brand signals high expertise and authority, it may be named by the artificial intelligence, even without ranking high in the organic results.

In-House Analytics and Direct Control

Running all operations and tooling internally gives Growing Search certain benefits. The company can update its analytics to adapt to changes in AI algorithms quickly. When AI search behavior shifts, there are no delays caused by waiting for outside vendors. This keeps its clients aligned with the latest ranking practices.

By owning all data pipelines and analytics platforms, Growing Search also reduces risk related to data privacy and quality. Insights from StakeView and BrandLens can be passed quickly to the consulting or editorial teams.

Recent industry studies confirm that agencies using custom tools report better tracking of AI citations and sentiment. This allows campaigns to shift as needed, sometimes before competitor actions or algorithmic updates would otherwise affect visibility.

Performance in Traditional and AI Search

Classical search engines still send many users to brand websites, but new data shows accelerated gains for those featured in AI answers. Quickly summarized AI Overviews cater to users looking for direct, authoritative responses. Brands mentioned or cited in these summaries attract more inquiries and an improved reputation.

Examples from ongoing research:

  •         Sites displayed in AI Overviews see upwards of 30% more brand mentions and a reported 20% increase in positive sentiment from users.
  •         Market share in these answer engines may be higher for brands with well-signaled trust markers, even over established competitors with better traditional ranks.
  •         Tools that track live citations and sentiment enable brands to respond to shifts within days or even hours, rather than weeks, as was often the case with older systems.

Why Sentiment and Citations Now Matter Most

AI-driven search engines have updated how they measure and rank authority. Recognition of entities and positive context is now a ranking factor. More weight is put on the sentiment AI models detect within content, and the strength of authority signals a brand projects.

Unlike older analytic tools that only tracked clicks or position in rank, BrandLens records both citation frequency and how the brand is discussed in AI answers. This approach tracks fine details. For example, a drop in positive mentions can be seen quickly. The client can respond immediately by adjusting how their brand or content appears. This rapid response helps manage risk during sensitive launches, events, or crises.

Evidence and Reported Results

Some results published by brands using Growing Search’s proprietary toolset show the effect of this detail-oriented approach:

  •         Brand mentions in AI Overviews can rise by 18% to 35% within six months once targeted content and authority adjustments are implemented.
  •         Early alerts show competitor names or products entering AI answer boxes before they reach traditional search rankings. This helps preemptively adjust marketing efforts.
  •         When sentiment in AI answers shifts negative or neutral, corrective steps can be applied and tracked for impact, supporting brand reputation at critical times.

Several reports from the first part of 2025 mark this approach as outperforming typical search optimization alone. Agencies not focused on tracking live AI mentions and sentiment are reported to miss emerging opportunities and suffer a loss of market share, especially now that over four in ten initial search interactions occur within AI-powered boxes.

What Brands Should Do Now

Brands that want reliable performance have clear steps, as seen from both case data and expert commentary:

  •         Use in-house analytics to monitor live share across regular and AI-driven search. Delayed or sampled data is less useful once AI results are updated frequently.
  •         Review and adjust internal content and authority markers. Ensure that expert signals and entities are consistently projected.
  •     Invest in tools that provide both quantitative insights (such as mention count) and qualitative feedback (such as sentiment) so that reputational risk can be managed directly.
  •         Focus on direct execution and internal expertise. Owning the data and workflow allows for prompt action as algorithms and platforms update their requirements.

Summary of Industry Findings

Agencies working with both search systems and artificial intelligence tools, supported by exclusive in-house analytics, are now driving the most measurable gains for brands. Platforms like StakeView and BrandLens provide timely, specific feedback. This helps manage brand presence in new AI Overviews as well as classic organic search. In-house execution remains essential for keeping pace with ongoing shifts in how answers are created and displayed.

Growing Search is an example of this approach. All work, from research to technical implementation, is handled by its own teams. The result is direct feedback, faster corrective cycles, and verifiable improvements in visibility and reputation.

As artificial intelligence systems mediate an increasing share of user discovery, brands need to focus on facts, measurement, and timely action. Agencies prepared for this with the right expertise and technology will keep their clients positioned at key points in the search journey.



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