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Services-as-Software: A New AI-Driven Paradigm for Professional Services

Services-as-Software (SaS), a term coined by Phil Fersht of HFS Research, is the shift from people-heavy projects and static software to AI-driven, outcome-focused services delivered like software. SaS is projected to become a $1.5T market by 2035 as software and services converge, reshaping how IT/BPO providers and advisory firms deliver value. It creates existential risk for “hours factories,” but also the biggest growth opportunity in a generation for firms that productize their expertise, embrace agentic AI, and move to scalable, subscription and outcome-based models.

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TL;DR — Services-as-Software (SaS), a term coined by Phil Fersht of HFS Research, is the shift from people-heavy projects and static software to AI-driven, outcome-focused services delivered like software. SaS is projected to become a $1.5T market by 2035 as software and services converge, reshaping how IT/BPO providers and advisory firms deliver value. It creates existential risk for “hours factories,” but also the biggest growth opportunity in a generation for firms that productize their expertise, embrace agentic AI, and move to scalable, subscription and outcome-based models.

Sources: HFS Research, HFS 1.5T projection, J.P. Morgan, Foundation Capital.

Definition: What is Services-as-Software?

Services-as-Software (SaS) describes a delivery model where business services are provided primarily through intelligent, AI-powered software rather than through large teams of people or rigid, one-size-fits-all apps. In SaS, enterprises consume outcomes (finance ops, IT ops, CX, analytics, risk, etc.) via adaptive, learning services—not via static licenses + armies of consultants.

See HFS overview: “Services-as-Software: Redefining How We Deliver Outcomes” (HFS Research).

Key traits (vs. traditional software and services), per HFS analysis of SaS vs. SaaS: workflows are dynamically generated by AI, interfaces are context-aware, and the service learns/optimizes continuously instead of relying on pre-set flows and manual interventions (HFS: Ditch same‑old SaaS).

Origin — The term Services-as-Software was coined by Phil Fersht, CEO of HFS Research, to capture the blurring of people-based services with technology (HFS team bio).

Why now? The drivers behind SaS

  • Stagnation of static SaaS: Many enterprise apps became bloated and rigid, forcing sameness and costly customization; buyers want outcomes, not shelfware (HFS on SaaS vs. SaS).
  • Inefficiency of labor-led services: Clients question paying for hours rather than results; they want speed, transparency, and automation (HFS SaS market note).
  • AI readiness: Agentic AI + observability + cloud integration finally make autonomous service delivery feasible at scale (HFS Agentic AI thesis).
  • Budget shifts & tech debt: Enterprises see SaS as a way to smash tech debt and redirect spend from headcount to AI-driven services; two‑thirds plan to replace significant human‑led services with AI‑led solutions within three years (HFS/Publicis Sapient report).
  • Capital flows: Investors frame SaS as AI’s third phase and a $3–5T opportunity across business services (J.P. Morgan Private Bank); VCs see a $4.6T SaS startup wave replacing white‑collar workflows (Foundation Capital).

How SaS differs from SaaS, Managed Services, and traditional IT/BPO

ModelWhat you buyHow value is deliveredScalabilityPricing
SaaSA product (features)You configure + integrate; often need servicesHigh, but often rigidPer‑user/license
Managed Services / BPOPeople + toolingProvider runs process with SLAs; labor-heavyScales with headcountFTEs, rate cards, SLAs
Consulting / AdvisoryExpertise, analysisProjects, decks, workshopsLimited by team sizeTime & materials, fixed fees
SaSOutcomes as a living serviceAI + automation + embedded IP that adapts continuouslySoftware-fast; “one‑to‑many”Subscriptions, usage, outcome-based

Deep-dive comparison: HFS on SaaS vs. SaS.

Market impact & size

HFS projects SaS will grow into a $1.5T market by 2035, absorbing spend from both IT services (which shrinks) and traditional software (which evolves toward AI‑driven services) (HFS projection; HFS market note).

Broader outlooks see an even larger prize as AI automates end‑to‑end business services across sectors—$3–5T in private markets, according to J.P. Morgan (link), and $4.6T in Services‑as‑Software companies across functions per Foundation Capital (link).

The great convergence: software “eats services” and services “become software”

SaS is collapsing the boundary between software vendors and services firms:

  • Software absorbing services: Platforms now ship with AI agents that take action, not just dashboards. Example: Salesforce Agentforce—autonomous, customizable agents that work across sales, service, marketing and more (Agentforce overview; GA announcement; Agentforce 3 update).
  • Services codifying into platforms: Global providers are productizing IP. IBM Consulting Advantage is an AI services platform and library of assistants that accelerates delivery and embeds repeatable software assets into engagements (press release; product page; independent coverage: Consultancy.uk, TechMonitor).
  • Strategy + AI engineering under one roof: McKinsey’s QuantumBlack (acquired 2015) exemplifies deep AI capability fused with consulting (acquisition blog; QuantumBlack today).

HFS frames success in SaS as mastering the three P’s: People, Products, Partners—retraining talent to work with AI, productizing know‑how as reusable software, and orchestrating ecosystems of tech/data partners (HFS webinar deck; HFS market note).

Implications for IT Services, BPO, and advisory firms

Pressure on billable hours: As routine build/run/operate work is automated, time‑and‑materials gives way to subscriptions and outcomes. HFS expects traditional IT services revenue to decline as SaS replaces labor in IT outsourcing, BPO and parts of consulting (HFS projection).

Client expectations reset: Buyers are signaling a pivot—two‑thirds plan to replace human‑led services with AI‑led alternatives within three years (HFS/Publicis Sapient). Analyst/advisory models are also under pressure to move beyond slow, paywalled reports toward real‑time, AI‑enhanced insight—see HFS’s take on the analyst industry’s “Blockbuster moment” (HFS).

Operating model overhaul: Firms must re-skill consultants to become AI‑augmented problem solvers, invest in platforms and reusable assets, and partner aggressively. Examples include IBM’s Advantage platform (see above) and hyperscaler/AI alliances across the major firms. Rankings show who is pushing ahead on AI, data and automation (e.g., HFS names Accenture, IBM, TCS, Wipro and others as market leaders) (Consultancy.eu).

New economics: The SaS model shifts firms from headcount‑linear revenue to product‑like margins and “one‑to‑many” scale. Early movers can capture share as spend migrates from FTEs to AI services. HFS calls SaS a “$1.5T opportunity,” not a death knell for incumbents who adapt (HFS bottom line).

Emerging business models (high level)

  • Subscription SaS
    Outcome‑oriented service bundles (e.g., “autonomous AP,” “AI service desk”) with tiers, usage add‑ons, and success SLAs.
  • Usage‑/events‑based
    Pay per case, ticket, transaction, or model‑inference volume for AI agents performing work.
  • Outcome‑/gain‑share
    Fees tied to quantified impact (cost‑to‑serve, cycle time, error rate, conversion, fraud loss avoided).
  • Hybrid (product + managed)
    Platform subscription plus light‑touch managed service for exceptions/governance.
  • IP licensing / enablement
    License core models/agents + playbooks to clients or partners to run SaS in their environments.
  • Ecosystem revenue
    Marketplace rev‑share for third‑party skills, connectors, domain packs.

Risk, governance, and trust

Automation risk (hallucinations, drift), data security, bias/compliance, and resilience require robust MLOps/AIOps, guardrails, and auditability. Providers can differentiate with transparency, human‑in‑the‑loop for edge cases, and regulatory alignment—turning governance into part of the service value. (See also J.P. Morgan’s framing of “services as software” as a durable, investable phase of AI with significant controls needs: JPM PB).

Playbook: Translating SaS for “hours factories” (IT & BPO providers, and broader professional services)

  • Pick your “living services.”
    Identify 3–5 offerings where your firm’s know‑how + data + workflows can be encoded into always‑on agents (e.g., IT incident auto‑resolution, invoice‑to‑pay, KYC onboarding, CX deflection/retention). Tie each to a clear, measurable outcome (MTTR, DSO, compliance breach rate, NPS, etc.).
  • Productize your expertise.
    Turn methods and accelerators into modular software assets (models, prompts, decision graphs, data pipelines, reference adapters). Treat P&L owners like product managers with roadmaps and telemetry.
  • Rewire the commercial model.
    Shift from hours to subscriptions/usage/outcomes; design success metrics and value sharing. Offer time‑boxed transitions (e.g., “90‑day SaS cutover”) to reduce client risk.
  • Blend human + machine.
    Define human‑in‑the‑loop roles (supervision, exception handling, change management). Upskill teams on agentic patterns, prompt engineering, evaluation metrics, and client‑specific tuning.
  • Build an ecosystem.
    Partner with AI platforms, hyperscalers, data providers, and industry ISVs to accelerate time‑to‑value. Create a marketplace for domain packs/connectors that complement your core SaS.
  • Instrument everything.
    Ship observability: success dashboards, latency/accuracy metrics, cost‑to‑serve, and explainability trails clients can audit.
  • Start with internal SaS.
    Use your own agents to automate proposal generation, research, delivery QA, code review, and knowledge reuse—lifting productivity while you learn how to run SaS reliably at scale. (Example of internal codification trend: IBM Consulting Advantage).
  • Message the value.
    Position SaS as fewer handoffs, faster outcomes, lower TCO, and continuous improvement—not as a tool sprawl. Back it with case metrics and transparent governance.

Beyond IT/BPO: Wider industry implications

SaS extends to finance, HR, supply chain, healthcare, legal, and more—anywhere standardizable knowledge work exists. Expect budget shifts from static tools and staff augmentation to AI services that directly execute work. HFS’s Pulse data and webinars point to a broad enterprise pivot toward SaS as a future‑proof operating model (HFS roundtable). Analyst/advisory models are also morphing (see HFS’s “Blockbuster moment” for the analyst industry: HFS).

Bottom line – and the opportunity for incumbents –

SaS is not the end of consulting or software—it is their fusion. The winners will be firms that fuse AI, automation, and domain expertise into scalable, outcome‑based services, moving beyond slideware and staff augmentation to living services that run the business every day. HFS calls it the “$1.5T opportunity”; J.P. Morgan and leading VCs see multi‑trillion‑dollar upside across business services. The time to build is now.

References & Further Reading

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