Canonical URL: https://elacelerador.es/en/cases-and-research/epam-ai-time-savings-customer-return/ --- description: The Altera case separates reported productivity, five-year forecasts and commercial value in EPAM’s artificial intelligence services. title: EPAM: from AI time savings to customer returns image: https://elacelerador.es/images/social/v1/epam-saving-time-ai-still-requires-showing-what-customer-gains-ce8aa78f46124a1cd0428089e70e211d.jpg --- 1. [Home](https://elacelerador.es/en/) 2. [Cases and research](https://elacelerador.es/en/cases-and-research/) # EPAM: saving time with AI still requires showing what the customer gains The Altera case separates reported task-time reductions from estimated five-year returns. That boundary determines what AI services can credibly promise buyers. By [Marian Vasile](https://elacelerador.es/en/author/marian-vasile/) 13 October 2026 at 08:55 CEST 4 min read [ Add as preferred source ](https://www.google.com/preferences/source?q=elacelerador.es&utm%5Fsource=elacelerador.es&utm%5Fcampaign=elacelerador.es) Share [ ](https://www.linkedin.com/sharing/share-offsite/?url=https%3A%2F%2Felacelerador.es%2Fen%2Fcases-and-research%2Fepam-ai-time-savings-customer-return%2F%3Futm%5Fsource%3Dlinkedin%26utm%5Fmedium%3Dsocial&utm%5Fsource=elacelerador.es&utm%5Fcampaign=elacelerador.es "Share on LinkedIn. 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Preview requests: 0") [ ](https://www.facebook.com/sharer/sharer.php?u=https%3A%2F%2Felacelerador.es%2Fen%2Fcases-and-research%2Fepam-ai-time-savings-customer-return%2F%3Futm%5Fsource%3Dfacebook%26utm%5Fmedium%3Dsocial&utm%5Fsource=elacelerador.es&utm%5Fcampaign=elacelerador.es "Share on Facebook. Preview requests: 0") ![Exterior of the EPAM building in Szeged, Hungary.](https://elacelerador.es/images/variants/v1/epam-saving-time-ai-still-requires-showing-what-customer-gains-exterior-building-w900.webp) EPAM building in Szeged, Hungary, 2018\. Company archive photograph; it does not document the Altera project. Framing adapted. Photo: [Aron96 · CC BY-SA 4.0](https://commons.wikimedia.org/wiki/File:Epam%5Fszeged.jpg?utm%5Fsource=elacelerador.es&utm%5Fcampaign=elacelerador.es) **In this report** 1. [Documentation starts a conversation about usable work](#article-section-documentation-starts-a-conversation-about-usable-work) 2. [The return horizon changes the promise](#article-section-the-return-horizon-changes-the-promise) 2 figures * [AI applications have more spending to justify](#article-figure-1) * [The buying decision includes business needs and expertise](#article-figure-2) [Download data (CSV)](https://elacelerador.es/en/download.csv?article=%2Fen%2Fcases-and-research%2Fepam-ai-time-savings-customer-return%2F) Chart values, table cells, source references and the report revision date. Altera developers report documentation-time reductions of up to 80%, according to EPAM’s published case . The same document estimates $3.4 million to $6.6 million in five-year returns from code and paralegal agents. The figures describe different kinds of evidence. A time reduction records a task. An estimated return adds assumptions about future use, costs and work the organisation can avoid or redirect. Commercial arguments become more precise when they preserve that separation: a customer can observe an operational improvement before confirming the full projected economic benefit. Aggregate spending gives context to that need for proof. Menlo Ventures’ estimate published by Statista puts departmental generative AI applications at $7.3 billion in the United States in 2025, against $1.8 billion in 2024\. A larger available budget raises the amount that needs justification; it does not turn Altera’s projected return into an already realized result. The data behind the story ### AI applications have more spending to justify Estimated US enterprise spending on generative AI applications, billion USD. Horizontal AIDepartmental AIVertical AI billion USD Tap or hover for details. Select a series above to show or hide it. Expand notesCollapse notes **Sources:** Statista; Original source Menlo combines a November 7–25, 2025 survey of 495 US enterprise decision-makers at companies already using AI with financial estimates. Figures are not the sample’s summed spending. The recast series excludes chips, inference and model serving, and AI features embedded in existing software. Explore the data table Scroll left or right to see all columns __AI applications have more spending to justify (billion USD)__ | Category | Horizontal AI | Departmental AI | Vertical AI | | -------- | --------------- | --------------- | --------------- | | 2023 | 0.3 billion USD | 0.2 billion USD | 0.1 billion USD | | 2024 | 1.6 billion USD | 1.8 billion USD | 1.2 billion USD | | 2025 | 8.4 billion USD | 7.3 billion USD | 3.5 billion USD | ## Documentation starts a conversation about usable work EPAM describes Altera using DIAL to understand legacy systems and produce documentation, and incorporating the platform into Note+. Its DIAL offering coordinates different AI models. The sale therefore combines a reusable technical foundation with work specific to the customer. The consequence for an enterprise account depends on what happens to the released hours. A team can answer more requests, accelerate a delivery or reduce contracted work. It can also retain spare capacity. Those choices affect revenue and costs differently even when the initial task finishes sooner. The person validating the purchase may not write the documentation. In Edelman and LinkedIn’s US study, 85% of internal decision-makers who are not specialist users consider understanding the business’s challenges and needs important. For EPAM, an accepted deliverable put to use helps explain value to those deciding budget, scope or compliance. The data behind the story ### The buying decision includes business needs and expertise Stated importance when selecting a vendor in an RFP, United States, 2025. Very or moderately important Tap or hover for details. All values are also available in the data table. Expand notesCollapse notes **Sources:** Statista; Original source Edelman and LinkedIn surveyed 1,934 executives March 17–April 3, 2025\. This chart covers the subgroup of internal decision-makers involved in buying without being expert users of the product; its size is not separately reported. Importance ratings, not contract win rates. Explore the data table Scroll left or right to see all columns __The buying decision includes business needs and expertise (%)__ | Category | Very or moderately important | | ------------------------- | ---------------------------- | | Understand business needs | 85% | | Understand industry | 76% | | Relevant expertise | 74% | | Strategic fit | 68% | | Cultural fit | 56% | | Safest choice | 41% | Commercial evidence needs to follow that conversion. In documentation, an accepted review enables another person to use the result. If it has to be rewritten, some of the time returns later. Examining the approved document and its subsequent use provides a more useful purchasing unit than counting agent-generated answers. The same distinction reaches marketing through EPAM’s email-personalisation accelerator , which incorporates preferences, purchase history and browsing behaviour into product recommendations. Preparing a message faster measures work; a customer using it to buy requires another proof. The offering’s value becomes clearer when message production and commercial response remain separate, just as the Altera case separates task time from estimated returns. ## The return horizon changes the promise EPAM’s five-year interval is an estimate for the Altera case, rather than audited profit already realised or a guarantee for other businesses. The 80% reduction is a reported maximum for documentation; it does not represent an 80% fall in all engineering costs. Keeping these conditions beside the figures preserves the evidence without expanding it. In another case, involving 1&1 , EPAM reports that the first agents went live within six months. That interval answers when use began; the return answers what changed economically. Faster deployment brings forward the opportunity to obtain value but does not establish its amount. For EPAM, further commercial growth has a firmer basis in engagements that can verify the sequence: an accepted task, work actually put to use and a measurable economic effect. Expanding adoption before establishing which pieces work multiplies spending and uncertainty together. A supportable promise starts with the usable result and reaches the money when the customer can demonstrate that step. [Back to top ↑](#article-top) ## In this article ### Sources and documents * [EPAM: Altera Digital Health case](https://www.epam.com/services/client-work/harnessing-ai-to-deliver-ongoing-value-with-dial?utm%5Fsource=elacelerador.es&utm%5Fcampaign=elacelerador.es) · www.epam.com * [EPAM DIAL platform](https://solutionshub.epam.com/solution/ai-dial?utm%5Fsource=elacelerador.es&utm%5Fcampaign=elacelerador.es) · solutionshub.epam.com * [EPAM: 1&1 customer-service case](https://www.epam.com/services/client-work/an-agentic-ai-customer-service-breakthrough?utm%5Fsource=elacelerador.es&utm%5Fcampaign=elacelerador.es) · www.epam.com * [EPAM: email-personalisation accelerator](https://www.epam.com/services/partners/salesforce/salesforce-marketing-cloud-personalization-accelerator?utm%5Fsource=elacelerador.es&utm%5Fcampaign=elacelerador.es) · www.epam.com * Statista * [Original methodology and data: Menlo Ventures / Statista](https://menlovc.com/perspective/2025-the-state-of-generative-ai-in-the-enterprise/?utm%5Fsource=elacelerador.es&utm%5Fcampaign=elacelerador.es) · Menlo Ventures / Statista * [Original methodology and data: Edelman / LinkedIn / Statista](https://www.edelman.com/sites/g/files/aatuss191/files/2025-07/2025%20Edelman-LinkedIn%20B2B%20Thought%20Leadership%20Impact%20Report%5FFINAL.pdf?utm%5Fsource=elacelerador.es&utm%5Fcampaign=elacelerador.es) · Edelman / LinkedIn / Statista Share [ ](https://www.linkedin.com/sharing/share-offsite/?url=https%3A%2F%2Felacelerador.es%2Fen%2Fcases-and-research%2Fepam-ai-time-savings-customer-return%2F%3Futm%5Fsource%3Dlinkedin%26utm%5Fmedium%3Dsocial&utm%5Fsource=elacelerador.es&utm%5Fcampaign=elacelerador.es "Share on LinkedIn. 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His work spans product marketing, SEO, paid advertising and deep online tracking, including behavioral analytics and attribution. ## Related articles [Cases and research](https://elacelerador.es/en/cases-and-research/) Analysis ### [SHIELD: a coupon’s cost depends on who claims it again](https://elacelerador.es/en/cases-and-research/shield-coupon-cost-accounts-legitimate-customers/) [Marian Vasile](https://elacelerador.es/en/author/marian-vasile/) 17 October 2026 6 min [Cases and research](https://elacelerador.es/en/cases-and-research/) Analysis ### [Safeguard Global: the calculator pricing two routes to expansion](https://elacelerador.es/en/cases-and-research/safeguard-global-calculator-eor-entity-expansion-cost/) [Marian Vasile](https://elacelerador.es/en/author/marian-vasile/) 17 October 2026 6 min [Cases and research](https://elacelerador.es/en/cases-and-research/) Analysis ### [AIOS and Bolt: a three-minute promise needs to explain the review that follows](https://elacelerador.es/en/cases-and-research/aios-bolt-consultation-approval-conversion/) [Marian Vasile](https://elacelerador.es/en/author/marian-vasile/) 17 October 2026 5 min **In this report** 1. 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