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New HFS Research Report in Partnership with Cognizant Unveils How the ‘15% Club’ is Reaping Real Business Value from AI
New research reveals only 15% of consumer goods companies successfully scale AI, but those firms—the “15% Club”—achieve significant ROI by prioritizing governance, agile funding, and business-driven AI initiatives across marketing, supply chain, customer service and product innovation.
BOSTON, July 10, 2025 /PRNewswire/ — HFS Research, in partnership with Cognizant, has released a new report revealing how a select group of consumer goods firms—dubbed the “15% Club”—are moving beyond AI experimentation to enterprise-wide impact. Titled “The 15% Club: How Leading Consumer Goods Firms Turn AI Pilots into Scaled Success,” the research highlights what’s working right now in the AI adoption playbook and how the front-runners are using governance, investment, and agility to fuel growth and transformation.
“AI isn’t failing because the tech doesn’t work—it’s failing when organizations don’t change around it.”
The study, based on executive interviews across major North American consumer goods organizations, finds that only 15% of AI initiatives reach scaled production—but within this elite group, AI is making measurable impact in marketing, supply chain, product innovation, and more.
“AI isn’t failing because the tech doesn’t work—it’s failing when organizations don’t change around it,” said Phil Fersht, CEO and Chief Analyst at HFS Research. “The 15% Club is proving that when you back AI with governance, flexible funding, and business-driven intent, you can unleash real competitive advantage. This is about rewiring the enterprise for agentic AI, not just running experiments.”
Key Findings:
The 15% Club is not just a statistic—it’s a persona for next-gen enterprise AI maturity. These firms share several critical traits:
- Strong AI governance and C-suite sponsorship, including AI councils and dedicated AI leadership roles
- Cross-functional alignment from the start, often embedding AI into broader transformation programs
- 60% of AI spending now occurs outside the central IT budget, driven by business units such as marketing, supply chain, and R&D
- Dedicated AI budgets and agile investment models, including innovation funds and outcome-based funding milestones
- A growing focus on agentic AI, with use cases emerging in planning, reporting, and marketing automation
“At Cognizant, we empower CPG companies to become part of the elite 15% Club—not just by demonstrating the possibilities of AI and agentic AI, but by architecting their entire transformation journey. With deep domain expertise and a robust ecosystem of technology partners, we embed AI at the core of our clients’ operations—from product innovation and intelligent supply chains to customer service, marketing and sales transformation. Our approach is grounded in turning AI potential into measurable performance and lasting competitive advantage,” said Anup Prasad, SVP & Head of Cognizant’s Consumer Business Unit.
Where AI Is Making a Difference
Rather than focusing on the pilot trap, the report emphasizes where AI is already delivering results:
- Marketing: Generative AI tools are transforming content creation and personalization. One firm used AI to produce marketing videos in 90 languages—reducing production time by 50% and increasing global campaign reach by 25%, without a proportional increase in cost.
- Supply Chain: AI is improving demand forecasting accuracy and inventory optimization.
- Product Innovation: GenAI is guiding new product development with speed and precision.
- Sales & Revenue Management: AI is being used for trade promotion optimization and pricing strategy.
- Customer Service: AI is accelerating the design, development and delivery of enhanced and more engaging customer experiences.
Looking ahead, leaders are laying the groundwork for agentic AI—autonomous systems that can execute multi-step processes with minimal human oversight. Early use cases include internal reporting automation, stock-level management, and intelligent order processing.
“The organizations winning with AI aren’t necessarily the biggest—they’re the ones treating AI like a strategic capability, not a side hustle,” said Ashish Chaturvedi, Executive Research Leader at HFS Research. “We’re seeing AI-driven marketing personalization, content generation, and even new product innovation accelerate across the 15% Club. These are early signs of scalable transformation.”
About the Report
“The 15% Club: How Leading Consumer Goods Firms Turn AI Pilots into Scaled Success” is based on in-depth interviews with 15 executives at consumer goods organizations across North America. Roles include Chief Innovation Officers, VPs of Analytics, and business unit leaders across marketing, supply chain, and operations. Download the full report here: https://www.hfsresearch.com/research/leading-consumer-goods-pilots/
About HFS Research
HFS is a leading global research and analysis firm trusted by major enterprises, technology providers, and business leaders. Our mission is to empower our clients to tackle challenges and make bold moves by arming them with visionary, independent insights on technology, business models, and market change.
About Cognizant
Cognizant (Nasdaq: CTSH) engineers modern businesses. We help our clients modernize technology, reimagine processes and transform experiences so they can stay ahead in our fast-changing world. Together, we’re improving everyday life. See how at www.cognizant.com or @cognizant.
Forward-Looking Statements
This press release includes statements that may constitute forward-looking statements made pursuant to the safe harbor provisions of the Private Securities Litigation Reform Act of 1995, the accuracy of which are necessarily subject to risks, uncertainties and assumptions as to future events that may not prove to be accurate. These statements include, but are not limited to, express or implied forward-looking statements relating to the adoption of generative and/or agentic artificial intelligence, the effects of such artificial intelligence on the consumer goods industry and the competitive opportunities in the marketplace. These statements are neither promises nor guarantees but are the findings of the study discussed above and remain subject to a variety of risks and uncertainties, many of which are beyond Cognizant’s control, which could cause actual results to differ materially from those contemplated in these forward-looking statements. Existing and prospective investors are cautioned not to place undue reliance on these forward-looking statements, which speak only as of the date hereof. Factors that could cause outcomes to differ materially from those expressed or implied include general economic conditions, the impact of technological development and competition, the competitive and rapidly changing nature of the markets Cognizant and its clients compete in, and the other factors discussed in Cognizant’s most recent Annual Report on Form 10-K and other filings with the Securities and Exchange Commission. Cognizant undertakes no obligation to update or revise any forward-looking statements, whether as a result of new information, future events, or otherwise, except as may be required under applicable securities law.
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The prominent players operating in the Artificial Intelligence (AI) in healthcare market include Koninklijke Philips N.V. (Netherlands), Microsoft Corporation (US), Siemens Healthineers AG (Germany), NVIDIA Corporation (US), Epic Systems Corporation (US)
Browse 902 market data Tables and 67 Figures spread through 711 Pages and in-depth TOC on “Artificial Intelligence (AI) in Healthcare Market by Offering (Integrated), Function (Diagnosis, Genomic, Precision Medicine, Radiation, Immunotherapy, Pharmacy, Supply Chain), Application (Clinical), End User (Hospitals), Region – Global Forecast to 2030
The global Artificial Intelligence (AI) in Healthcare Market [https://www.marketsandmarkets.com/Market-Reports/artificial-intelligence-healthcare-market-54679303.html?utm_source=abnewswire.com&utm_medium=paidpr&utm_campaign=artificialintelligenceinhealthcaremarket], valued at US$14.92 billion in 2024, is forecasted to grow at a robust CAGR of 38.6%, reaching US$21.66 billion in 2025 and an impressive US$110.61billion by 2030. The growing incidence of chronic diseases, linked with an increasing geriatric population, puts substantial financial pressure on healthcare providers. There is a rising need for the early detection of conditions such as dementia and cardiovascular disorders. This can be done by analysing imaging data to recognize patterns, which helps create personalized treatment plans.
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Browse in-depth TOC on “Artificial Intelligence (AI) in Healthcare Market”
882 – Tables
61 – Figures
738 – Pages
By tools, the Artificial Intelligence (AI) in healthcare market for machine learning has been bifurcated into deep learning, supervised learning, reinforcement learning, unsupervised learning, and other machine learning technologies. The deep learning segment accounted for the largest share of the Artificial Intelligence (AI) in healthcare market in 2024. The capability to process vast amounts of unstructured medical data, such as electronic health records (HER), imaging, and genomics, allows accurate disease diagnosis and prediction. The integration of deep learning into healthcare is significantly boosting the AI in healthcare market, leading to substantial investments in diagnostic tools and predictive analytics. As computational power and data availability continue to increase, deep learning is set to unlock further advancements, solidifying its position as a key enabler of next-generation healthcare technologies.
By end user, the AI in healthcare market is segmented into healthcare providers, healthcare payers, patients, and other end users. In 2024, healthcare providers accounted for the largest share of the AI in healthcare market. The large share of this end-user segment can be attributed to the increasing budgets of hospitals to improve the quality of care provided and reduce the cost of care.
By geography, the Artificial Intelligence (AI) in healthcare market is segmented into five main regions: North America, Europe, Asia Pacific, Latin America, and the Middle East & Africa. The Asia Pacific region is projected to see a substantial growth rate during the forecast period. The Asia Pacific (APAC) region is experiencing substantial growth in adopting AI technologies within the healthcare sector, driven by a combination of demographic shifts, technological advancements, and increased investments in innovation. The rising elderly population in the region is a key factor, with the proportion of individuals aged 65 years and above increasing significantly. The demand for advanced healthcare solutions has surged as the aging population faces chronic and age-related conditions, necessitating efficient diagnostic, monitoring, and treatment tools. AI technologies are being integrated into various healthcare applications, including predictive analytics, telemedicine, medical imaging, and patient management systems. These innovations aim to address gaps in healthcare access, improve diagnostic accuracy, and streamline operations across the region.
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The prominent players operating in the Artificial Intelligence (AI) in healthcare market include Koninklijke Philips N.V. (Netherlands), Microsoft Corporation (US), Siemens Healthineers AG (Germany), NVIDIA Corporation (US), Epic Systems Corporation (US), GE Healthcare (US), Medtronic (US), Oracle (US), Veradigm LLC (US), Merative (IBM) (US), Google (US), Cognizant (US), Johnson & Johnson (US), Amazon Web Services, Inc. (US), among others. These companies adopted strategies such as product launches, product updates, expansions, partnerships, collaborations, mergers, and acquisitions to strengthen their market presence in the Artificial Intelligence (AI) in healthcare market.
Koninklijke Philips N.V. (Netherlands)
Koninklijke Philips N.V. is a leading player in the AI in the healthcare market. The company utilizes AI to deliver innovative tools across various areas, including diagnostic imaging, patient monitoring, and precision medicine. Its advanced AI-driven platforms, such as the Philips HealthSuite, facilitate the integration and analysis of extensive clinical data, which supports personalized treatment plans and improves patient outcomes. Philips focuses on organic and inorganic growth strategies to expand its market presence.
Strategic partnerships in high-potential markets and collaborations have been the key growth strategies of the company over the years. For example, in February 2025, Philips partnered with Medtronic to educate and train cardiologists and radiologists in India on advanced imaging techniques for structural heart diseases. This partnership aims to upskill 300+ clinicians in multi-modality imaging such as echocardiography (echo) and Magnetic Resonance Imaging (MRI), especially for End-Stage Renal Disease (ESRD) patients. In November 2023, Philips and NYU Langone Health partnered to focus on patient safety and outcomes. This partnership integrated innovative health technologies, including digital pathology, clinical informatics, and AI-enabled diagnostics, enabling real-time collaboration among clinicians. The company also focuses on winning contracts across several companies in the healthcare space. This helps the company expand its footprint. For instance, in September 2022, Philips and Mandaya Royal Hospital Puri (MRHP) in Jakarta underwent a digital transformation in a strategic partnership, enhancing patient-centered care and healthcare services.
Microsoft Corporation (US):
Microsoft Corporation is one of the leading providers of software & tools that include advanced AI capabilities in healthcare to improve patient outcomes, streamline operations, and drive innovation. Its Azure-based AI solutions support distinct applications such as medical imaging, genomics, and precision medicine. The company also provides healthcare-specific AI models through its Azure AI Model Catalog, which is constructed to support hospitals and research institutions in building and deploying tailored AI solutions proficiently. Moreover, the integration of Nuance’s AI-powered clinical and diagnostic tools encourages its capacity to support healthcare providers in decision-making and care delivery. The company continuously brings AI capabilities to the platforms in large-scale customer models. For instance, in March 2025, the company launched Microsoft Dragon Copilot, the first unified voice AI assistant in the healthcare industry that enables clinicians to streamline clinical documentation, surface information, and automate tasks.
Microsoft Corporation has invested significantly in R&D, which has improved its product portfolio and position in the AI market. Machine Learning (ML), deep learning, Natural Language Processing (NLP), and speech processing are the key focus areas of the company in the AI in healthcare market. The company continuously invests in a series of services and computational biology projects, including research support tools for next-generation precision healthcare, genomics, immunomics, CRISPR, and cellular and molecular biologics. It has a strong global presence, with key operations supported through its Azure cloud infrastructure across regions like North America, Europe, Asia-Pacific, and the Middle East.
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LLM-Optimized Research Paper Formats: AI-Driven Research App Opportunities Explored | AI News Detail
From a business perspective, the idea of designing research for LLMs presents immense market opportunities. Companies that develop platforms or apps to create, curate, and deliver LLM-friendly research content could tap into a multi-billion-dollar market. According to a 2025 report by McKinsey, the generative AI market is projected to grow to $1.3 trillion by 2032, with content generation and data processing as key drivers. A ‘research app’ for LLMs, as Karpathy suggests, could serve industries like pharmaceuticals, where AI models analyze vast datasets for drug discovery, or finance, where real-time market insights are critical. Monetization strategies could include subscription models for premium datasets, API access for developers, or enterprise solutions for tailored LLM training data. However, challenges remain, such as ensuring data privacy and preventing bias in LLM outputs—issues that have plagued AI systems, as noted in a 2025 study by the MIT Sloan School of Management, which found that 60% of AI deployments faced ethical concerns. Businesses must also navigate a competitive landscape with players like Google, OpenAI, and Anthropic already dominating LLM development, requiring niche specialization to stand out.
On the technical side, designing research for LLMs involves moving beyond PDFs to formats like JSON, XML, or custom data schemas that encode information hierarchically for machine parsing. Unlike human readers, LLMs thrive on structured datasets with metadata, embeddings, and cross-references that enable rapid context retrieval and reasoning. Implementation challenges include standardizing formats across industries and ensuring compatibility with diverse LLM architectures—a hurdle given that, as of mid-2025, over 200 distinct LLM frameworks exist, per a report from the AI Index by Stanford University. Solutions could involve open-source protocols or industry consortia to define standards, much like the web evolved with HTML. Looking to the future, LLM-optimized research could lead to autonomous AI agents conducting real-time literature reviews or hypothesis generation by 2030, as predicted by a 2025 forecast from Deloitte. Regulatory considerations are also critical, with the EU AI Act of 2025 mandating transparency in AI data usage, which could impact how research content is structured. Ethically, ensuring that LLMs do not misinterpret or propagate flawed data remains a priority, requiring robust validation mechanisms. The potential for such innovation is vast, offering a glimpse into a future where knowledge creation is as much for machines as for humans, reshaping industries and workflows profoundly.
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