PUBLISHED DATE: 2025-08-13 12:05:32

HFS Horizons Report: Generative Enterprise™ Services, 2023

October 2023

Authors:

Excerpt for Publicis Sapient

Introduction: The HFS Value Chain and Market Dynamics

This HFS Horizons: Generative Enterprise™ Services, 2023 report is the industry’s first competitive analysis of professional services firms and the value they create with enterprise clients adopting and experimenting with generative AI (GenAI) technologies.

HFS’ Generative Enterprise™ articulates the pursuit of AI technologies based on large language models (LLMs) like ChatGPT and GPT-4 to reap significant business benefits for organizations—continuously generating new ideas, redefining how work gets done, and disrupting business models steeped in decades of antiquated process and technology.

The report examines and assesses 35 service providers, evaluating their capabilities to understand the Why, What, How, and So What of their Generative Enterprise services offerings. Detailed profiles of each service provider are included, outlining provider facts, strengths, and development opportunities.

This research is based on briefings from each participant, publicly available announcements, data points, and case studies. An open call for participation resulted in unprecedented engagement. Each participant provided customer and partner references, and their responses, along with supplementary customer reference data, ensure the voice of the customer impacts the outcomes. Where a service provider chose not to brief us, profiles and scores were created from publicly available information and regular conversations with industry leaders.

Executive Summary

1. The Generative AI Gold Rush: A $7 Trillion Prize

Generative AI’s (GenAI) adoption has been unprecedented—ChatGPT reached 100 million users in two months, compared to RPA’s decade-long journey to 15 million. Boardrooms everywhere are demanding action on GenAI, prompting a gold rush among service providers. Leading systems integrators and consultancies have rapidly established new practices, divisions, platforms, and partnerships, investing billions and training thousands. This journey is just beginning.

2. Point Solutions Dominate—But Not for Long

AI budgets are rapidly shifting to GenAI projects, averaging 41% across surveyed enterprises. Most current efforts are point solutions in POCs and pilots, solving specific tasks. As budget cycles progress, we expect increased investment to take GenAI deeper into end-to-end processes, shaping new ways of working. The next step will be more challenging but more rewarding.

3. Disruption Hits CX, EX, and Sales/Marketing First

Enterprise leaders are prioritizing GenAI for customer experience (CX), employee experience (EX), and sales/marketing. While code transformation is a leading use case among service providers, it appears in only about 10% of case studies. Most case studies are proofs of concept or pilots, with few demonstrating ROI. At this stage, enterprises are satisfied with softer measures like time-to-serve, CSAT, or time-to-market.

4. Tech Know-How vs. Business Transformation

Customers see a gap between service providers’ tech implementation skills and their ability to drive business transformation. As enterprises seek help beyond initial point solutions, this gap must close. Many service providers are focusing on internal GenAI transformation to build credentials for guiding clients.

5. The Revolution is Personal—Get Hands-On

Using GenAI tools is essential for personal understanding and due diligence. Leaders must develop GenAI muscle memory to envision the future through today’s technology, not past experience.

The New S-Curve: An Inflection Point for IT and Business Services

The Generative Enterprise inspires a new S-curve of value creation for IT and business services. Traditional outsourced services are likely to lose momentum in favor of AI-led, data-driven services focused on growth and trust. Successful relationships must be performance- and purpose-driven, with hybrid pricing and innovation funds proving value.

Leading IT and business services firms made over 50 GenAI-related announcements in just two months in early 2023, primarily focused on expanding hyperscaler partnerships.

The Generative Enterprise and widespread GenAI application can manage the Digital Dichotomy—balancing macroeconomic slowdown with the urgent need to innovate. Data and AI are colliding, creating and destroying value rapidly. Without quality data, AI benefits won’t scale, and scaling to the ecosystem will require increasingly private data.

Stages of GenAI value creation depend on data nature and technology maturity, with impacts extending beyond productivity. GenAI will disrupt creativity and ideation, not just rote tasks. The road ahead is challenging, with ten key challenges every enterprise must consider.

Enterprise Expectations: EX, CX, Innovation, and Productivity

How do you expect GenAI to impact company business economics over the next 12-18 months?

The Generative Enterprise: A New S-Curve of Value Creation

The IT and business services industry is at an inflection point, jumping to a new S-curve of value creation:

Global Enterprise (People Driven):

Generative Enterprise™ (AI Driven):

GenAI Adoption: Consumer-Led, Enterprise-Driven

Road to 100 Million Users:

The pressure is on enterprise leaders to join the GenAI rush, driven by both top-down (shareholders, boardrooms) and bottom-up (employees using ChatGPT and other apps) forces.

RPA vs. ChatGPT Users (2012–2023):

GenAI: A Different Kind of Disruption

Why is GenAI different from other recent tech disruptions?

GenAI in Healthcare: Transforming the Value Chain

Health Insurance Value Chain:

Healthcare Provider Value Chain:

Business Functions: Where GenAI Will Create Value

Top Three Functions for GenAI Value (Next 12–18 Months):

Managing the Digital Dichotomy: Slowdown vs. Big Hurry

Cost savings are important but insufficient for leadership longevity. Ambitious C-suites must seek new value sources to stay competitive. Investment in Generative Enterprise opportunities bridges the gap between macroeconomic headwinds (the Slowdown) and the urgent need to innovate (the Big Hurry).

Data Access: The Key to Redefining Ecosystems

Trust between data owners will control the value that maturing GenAI and AI deliver. The journey spans three horizons:

Data sources evolve from public to private (individual and enterprise) as GenAI matures.

GenAI’s Impact: Beyond Productivity

HFS Enterprise Innovation Framework:

GenAI’s Impact Across Horizons:

The Role of Data, OneOffice, and OneEcosystem

Stages of GenAI Value Creation:

The GenAI Ecosystem: Unfolding Rapidly

Apps: Consumer (entertainment, productivity), enterprise stack (productivity, admin, sales, marketing, IT/security, industry verticals, creative, health, defense, agriculture, construction), enterprise applications (Adobe, Salesforce, SAP, etc.)

Infrastructure: Deploy/monitor (Hugging Face, arize), train/fine-tune (Weights & Biases, PyTorch), open-source models (LLAMA, Stanford Alpaca), full-stack LLMs (OpenAI, Anthropic), data storage/processing (Snowflake, Databricks), cloud (AWS, Azure, Google Cloud), hardware (NVIDIA, AMD, Intel)

The Enterprise Journey: 10 Challenges

  1. Most GenAI examples are not enterprise-centric; few projects are in production.
  2. Arms race to build foundational models; risk of a bubble.
  3. Power concentrated with hyperscalers; frustration with oligopoly.
  4. New ecosystem (Nvidia, Databricks, startups); navigation challenges.
  5. Governance/integration are key; privacy laws and legislation looming.
  6. FTC investigation into OpenAI.
  7. Most use cases use public data; sharing private data is challenging.
  8. Singular focus on productivity is misleading.
  9. Tech evolves rapidly; enterprises still struggle with cloud adoption.
  10. AI’s carbon footprint debate is just starting.

Research Methodology

Service Providers Covered

A comprehensive list of 35 providers, including Accenture, Capgemini, Cognizant, Deloitte, EY, IBM, Infosys, KPMG, Publicis Sapient, PwC, TCS, Wipro, and others.

Generative Enterprise Services Value Chain

Technology Ecosystem

Data Sources

Assessment Methodology

Providers are evaluated on:

Demographics and Customer/Partner Data

Customer Ratings (out of 10):

Partner Ratings (out of 10):

Talent and Commercial Models:

HFS Horizons Results: Generative Enterprise™ Services, 2023

Summary of Providers (Selected Highlights)

HFS Horizons for Generative Enterprise Services, 2023

Horizon 3 Market Leaders demonstrate strong GenAI/LLM capabilities, frameworks for responsible/ethical AI, co-creation with partners, and are recognized as thought leaders.

Horizon 2 Innovators focus on breaking down data silos, improving decision-making, and have market-ready AI tools.

Horizon 1 Disruptors are strong in ML, technical skills, and implementation.

Publicis Sapient Profile: Generative Enterprise™ Services, 2023

Horizon 3 – Market Leader

Strengths:

Development Opportunities:

Key Offerings:

M&A (2019–2023):

Partnerships:

Key Clients:

Global Operations:

Flagship IP:

Further Reading: Primers, Advice, and Guidance for GenAI

HFS Research Authors

Phil Fersht, CEO and Chief Analyst

David Cushman, Executive Research Leader

Saurabh Gupta, President, Research and Advisory

Niti Jhunjhunwala, Senior Analyst

About HFS

HFS is a leading global research and analysis firm trusted by executive leadership. Our mission is to help clients tackle challenges, make bold moves, and bring big ideas to life with accurate, visionary, and thought-provoking insight. Our analysts have deep, real-world experience and are respected for their independent, no-nonsense perspectives. Our goal: to propel you to success.

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