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IBM Software / SaaS global

IBM Chief Sustainability Office

Sales Automation

IBM's Chief Sustainability Office was fielding growing volumes of complex sustainability-data requests, but fragmented systems and manual research slowed seller support and limited the team's ability to scale.

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$50M in sales pipeline influenced in the first four months
50 data sources unified into one conversational experience
From days to seconds

Reported impact

Business outcome

AskSustainability reduced response times from days to seconds, supported a meaningful portion of IBM's seller pipeline and gave the sustainability office a scalable way to support both revenue and compliance-oriented data requests.

  • Productivity Improvement
  • Revenue Growth
  • Speed to Market

Solution

IBM built AskSustainability as an AI-powered agent so sustainability expertise could be delivered on demand instead of through ad hoc specialist work. The solution uses IBM watsonx.ai and IBM watsonx Orchestrate to act as an institutional expert over sustainability metrics, policies and client-specific product carbon-footprint data. Rather than forcing sellers or internal teams to search multiple fragmented systems, the agent provides trusted natural-language answers from a centralized knowledge base and plugs into the places where users already work, including AskSales, AskIBM and Slack. This design combines knowledge retrieval, response automation and workflow distribution in a single operating model: watsonx.ai supports the answer-generation layer, watsonx Orchestrate enables the agent behavior and delivery, and the surrounding hubs expose the capability broadly across IBM. The result is a sales- and operations-facing sustainability assistant that turns specialist knowledge into a scalable self-service asset.

Data flow

Sustainability metrics, policies and client-specific product carbon-footprint data are centralized for AskSustainability, watsonx.ai generates the response, and the agent is delivered through AskSales, AskIBM and Slack where users consume the answers.

Solution architecture

2 components · 2 layers
  1. Compute
    • IBM watsonx.ai Generates trusted natural-language responses over sustainability metrics, policies and product-footprint data.
  2. Orchestration
    • IBM watsonx Orchestrate Runs the AskSustainability agent and helps distribute it across IBM's existing work hubs.

Architecture clues

  • Integration into AskSales, AskIBM and Slack was part of the initial rollout, not a later add-on.
  • The agent is positioned as an institutional expert rather than only a search interface.
  • The solution focuses on trusted data such as operational metrics, policies and product carbon footprints.

Evidence from the source

Automated responses reduced turnaround times from days to seconds
IBM watsonx Orchestrate
IBM watsonx.ai
an estimated $50 million in sales pipeline
Transparency Evidence & methodology 75/100 reference value · 87% confidence · 1 source

Review how this reference was scored and trace each normalized claim back to its documented source.

01

Scoring methodology

How scores are calculated

Customer Reference Value measures usefulness as a customer reference. Evidence Confidence measures the quality and traceability of available evidence, not independent verification.

Customer reference value75/100
  • Problem clarity20/20
    Measures whether the customer's operational problem is specific enough to compare.
  • Implementation depth25/25
    Rewards named components, data flow, integrations, and architecture detail.
  • Outcome specificity20/20
    Measures whether the reported benefit is concrete rather than a generic claim.
  • Quantified impact0/25
    0 metrics describe measurable impact.
  • Deployment scale10/10
    Rewards evidence of a live or scaled deployment and meaningful integration scope.
Evidence confidence87%
  • Source authority20/25
    The main evidence is an official vendor-published customer story.
  • Claim traceability21/25
    10 of 12 key fields link to a named source.
  • Direct evidence20/20
    4 direct source quotes retained.
  • Date provenance10/10
    The publication date comes from the source page or publisher.
  • Source transparency8/10
    1 source reference document publisher, URL, authority, retrieval, and supported fields.
  • Implementation specificity8/10
    Rewards source-backed components, data flow, quantified impact, and a specific outcome.
02

Traceability

Sources & provenance

Field coverage shows which facts each source supports. Dates are shown only when documented by the source.

  1. IBM

    IBM Chief Sustainability Office customer story

    First-party
    https://www.ibm.com/case-studies/cso-asksustainability
    Source type
    Vendor-published customer story
    Published
    Jun 17, 2026
    Supports
    • Customer
    • Business problem
    • Solution
    • Products
    • Solution components
    • Data flow
    • Integrations
    • technical area
    • use case category
    • Business outcome
    • outcome category
    • Metrics
    • Architecture
    • evidence quotes
    • Publication date

Date evidence

Not separately sourced Industry, Region, Company size. Treat these normalized attributes as lower-confidence until a dedicated source is added.

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