AIM Research · specialised in data and AIIndependent · Analyst-led · Vendor-neutral

    PeMa Quadrant · 1st edition · Published May 22, 2026

    GCC AI Impact Series - From Hype to ROI: Realising Enterprise Value From GenAI and Agentic AI in GCCs

    35 vendors evaluated on market penetration and technology maturity. 17 qualify as Leaders.

    35

    Vendors evaluated

    17

    Leaders

    First edition of this PeMa Quadrant.

    17 Leaders · 9 Seasoned · 9 Challengers

    GCC AI Impact Series - From Hype to ROI: Realising Enterprise Value From GenAI and Agentic AI in GCCs report cover

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    Explore Platforms

    The PeMa Quadrant

    Where all 35 vendors landed

    Hover a dot for the vendor, click to open its passport.

    Technology maturity →
    SeasonedLeadersChallengersGrowth

    Market penetration →

    2025

    Positions from 2025 are read from the chart AIM published that year. Source →

    What the report finds

    5 shifts buyers should know

    01

    The most successful AI implementations are inward-facing, focusing on productivity gains in developer workflows and enterprise knowledge systems.

    Finding 1 of 5

    02

    Customer-facing AI adoption is limited due to regulatory, trust, and accountability concerns.

    03

    Organizations seeing progress are those deliberately slowing down to fix data fragmentation and rethink processes.

    04

    Governance and accountability are crucial and should be defined upfront rather than as afterthoughts.

    05

    The defining question for leaders is whether they are willing to confront foundational gaps that determine AI success.

    Vendors evaluated

    All 35 vendors, and how they moved

    VendorPlacementHeadquartersVendor passport
    AccentureLeaders—Passport →
    ANSRLeaders—Passport →
    Capgemini Leaders—Passport →
    CGILeaders—Passport →
    CognizantLeaders——
    DeloitteLeaders—Passport →
    EYLeaders—Passport →
    HCL Technologies (HCLTech)Leaders—Passport →
    HexawareLeaders—Passport →
    IBMLeaders—Passport →
    InfosysLeaders—Passport →
    KPMG IndiaLeaders—Passport →
    PwC IndiaLeaders—Passport →
    Tech MahindraLeaders—Passport →
    VestianLeaders—Passport →
    WiproLeaders—Passport →
    ZinnovLeaders——
    Fidel SoftechSeasoned——
    MindPool Tech.Seasoned——
    NexdigmSeasoned——
    NLB ServicesSeasoned——
    OpteamixSeasoned——
    SRKay ConsultingSeasoned——
    Systems PlusSeasoned——
    Torry HarrisSeasoned——
    Yash TechnologiesSeasoned——
    Ace SoftwareChallengers——
    Astravise ServicesChallengers——
    BridgePath InnovationsChallengers——
    Cushman & WakefieldChallengers——
    JSS ProChallengers——
    SA TechnologiesChallengers——
    SansoviGCC by GoodWorksChallengers——
    TekWissenChallengers——
    TrueFirmsChallengers——
    CGILeaders
    CognizantLeaders
    ——
    EYLeaders
    IBMLeaders
    ZinnovLeaders
    ——
    Fidel SoftechSeasoned
    ——
    MindPool Tech.Seasoned
    ——
    NexdigmSeasoned
    ——
    NLB ServicesSeasoned
    ——
    OpteamixSeasoned
    ——
    SRKay ConsultingSeasoned
    ——
    Systems PlusSeasoned
    ——
    Torry HarrisSeasoned
    ——
    Yash TechnologiesSeasoned
    ——
    Ace SoftwareChallengers
    ——
    Astravise ServicesChallengers
    ——
    BridgePath InnovationsChallengers
    ——
    Cushman & WakefieldChallengers
    ——
    JSS ProChallengers
    ——
    SA TechnologiesChallengers
    ——
    SansoviGCC by GoodWorksChallengers
    ——
    TekWissenChallengers
    ——
    TrueFirmsChallengers
    ——

    Showing 10 of 35 ·

    Abstract

    This white paper explores the adoption and impact of Agentic AI in Global Capability Centres (GCCs) across sectors like Retail, BFSI, Healthcare, and Life Sciences.

    Despite significant investments in Generative and Agentic AI, results are uneven due to readiness issues rather than ambition. Through discussions with over 40 CXOs and technology leaders in Bengaluru, Mumbai, and Hyderabad, a pattern emerged: organizations are often moving faster than their platforms and data can support, leading to technical debt. Successful implementations focus on internal productivity gains in developer workflows, enterprise knowledge systems, and complex process orchestration, while customer-facing adoption lags due to regulatory, trust, and accountability concerns. The report challenges the notion that Agentic AI success is about speed or scale, emphasizing the importance of addressing foundational gaps like data fragmentation, process inefficiencies, and governance. The transition in India’s GCC ecosystem is highlighted, moving from delivery engines to accountable owners of platforms, products, and outcomes, with a focus on deliberate, well-governed AI deployment.

    Methodology

    How vendors were scored

    The research was conducted through closed-door conversations with over 40 CXOs and senior technology leaders across Bengaluru, Mumbai, and Hyderabad.

    X axis

    Market penetration

    • Delivery scale
    • Financial health
    • Customer mindshare

    Y axis

    Technology maturity

    • Technical innovation
    • Value realisation
    • DataOps depth

    The research was conducted through closed-door conversations with over 40 CXOs and senior technology leaders across Bengaluru, Mumbai, and Hyderabad. The study focused on sectors such as Retail, BFSI, Healthcare, and Life Sciences. Publicis Sapient, in partnership with AIM Research, facilitated these discussions to identify patterns in AI adoption, challenges, and successful strategies. The evaluation approach centered on understanding organizational readiness, governance structures, and the transition from experimentation to impactful AI deployment.

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    Frequently asked questions

    The PeMa (Penetration and Maturity) Quadrant is AIM Research's 2x2 vendor evaluation framework. It measures each provider's market penetration (clients, deal sizes, geographic spread) and technology maturity (capabilities, platforms, partnerships), and places them as Leaders, Seasoned Vendors, Growth Vendors or Challengers.

    Any enterprise technology vendor active in the relevant market category can request to participate. AIM Research issues an open RFI for each study and invites qualifying vendors via the Research Calendar.

    Vendors are evaluated through a structured RFI process backed by primary research, including vendor briefings, customer references and product evaluations. They are scored across 40+ weighted criteria covering product capabilities, strategy and market impact, and the weighted scores are mapped to one of the four quadrant positions.

    The date of the next edition has not been announced yet. Upcoming studies and their RFI windows are listed on the AIM Research Calendar.

    The main barriers include data fragmentation, process inefficiencies, and a lack of governance and accountability structures. Organizations often move faster than their platforms and data can support, leading to technical debt and uneven results.

    Successful implementations focus on internal productivity gains, such as improving developer workflows and enterprise knowledge systems. These organizations deliberately slow down to fix foundational issues like data fragmentation and process inefficiencies before deploying AI.

    Customer-facing AI adoption is limited due to concerns about regulation, trust, and accountability. Organizations are cautious about deploying AI in customer interactions due to the potential risks and the need for strong governance frameworks.