Reported impact
Business outcome
With Copilot's introduction, OPAP aims to save time and automate routine tasks, as well as make meetings more actionable, efficient, and quick.
- Productivity Improvement
- Speed to Market
MicrosoftMedia and EntertainmentEnterprise Knowledge SearchIT Operations AutomationAI and Machine LearningGenerative AI / LLMProductivity ImprovementSpeed to Market2024 MicrosoftMS#0078d4Media and EntertainmentGreeceOPAP, Greece's leading gaming company, was one of the first companies globally to integrate Microsoft Copilot to transform its daily workflows.Copilot for Microsoft 365 emerged as a solution.” Alexia Mantou, Digital Business Specialist, OPAP OPAP…May 7, 20245Enterprise Knowledge Search|IT Operations AutomationMicrosoft 365 · Microsoft Copilot for Microsoft 365 · Microsoft Teams0 2024-05-07 5
Opap
Enterprise Knowledge Search · IT Operations Automation
OPAP, Greece's leading gaming company, was one of the first companies globally to integrate Microsoft Copilot to transform its daily workflows.
Copilot for Microsoft 365 emerged as a solution.” Alexia Mantou, Digital Business Specialist, OPAP OPAP deployed Copilot for Microsoft 365 through a change management process, with a team of Digital Change Ambassadors at its core.
Founded in 1958, OPAP is the leading gaming company in Greece and one of the most renowned in the industry worldwide.
OPAP recently introduced an initiative to simplify the everyday life of its people.
These ambassadors are instrumental in cascading knowledge, addressing employee inquiries, and providing support to ensure smooth adoption of new digital technologies, including Copilot.
Solution
Opap rolled out Microsoft 365 across its Microsoft 365 estate because OPAP, Greece's leading gaming company, was one of the first companies globally to integrate Microsoft Copilot to transform its daily workflows. Users work inside applications such as Microsoft 365, Microsoft Copilot for Microsoft 365, and Microsoft Teams, where the assistant can summarize meetings and email, draft documents, surface answers from existing files and conversations, and help employees move from context gathering to action without switching tools. Rather than building a separate chatbot, the organization grounded AI in the same collaboration data, permissions, and operational workflows that staff already use every day, which keeps adoption and governance aligned. The result is a reusable productivity layer for knowledge work and service delivery, and With Copilot's introduction, OPAP aims to save time and automate routine tasks, as well as make meetings more actionable, efficient, and quick.
Data flow
Employee prompts entered in Microsoft 365 apps are grounded in the user’s permitted files, conversations, and meeting context, then returned in the same workflow as summaries, drafts, or answers that staff can act on immediately.
Solution architecture
- Serving
- Microsoft Copilot for Microsoft 365 Grounds prompts in Microsoft 365 content so employees can summarize meetings and email, draft documents, and retrieve answers without leaving daily workflows.
- Microsoft Teams Hosts collaboration, meetings, and chat workflows where users consume summaries, updates, and shared operational context.
- Uncategorized
- Microsoft 365 Supports a specific part of the customer’s Microsoft-based implementation.
Architecture clues
- Founded in 1958, OPAP is the leading gaming company in Greece and one of the most renowned in the industry worldwide.
- Primary implementation components: Microsoft 365, Microsoft Copilot for Microsoft 365, Microsoft Teams
- With the latest developments in GenAI and the productivity boost it promises, the company started investigating how this can also benefit its employees.
Evidence from the source
“We wanted to empower our people to utilize technologies that would allow them to become more efficient, save time, and focus on things that are much more valuable and more enjoyable than repetitive work. Copilot for Microsoft 365 emerged as a solution.”
Transparency Evidence & methodology
Review how this reference was scored and trace each normalized claim back to its documented source.
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 value70/100
- Problem clarity20/20Measures whether the customer's operational problem is specific enough to compare.
- Implementation depth20/25Rewards named components, data flow, integrations, and architecture detail.
- Outcome specificity20/20Measures whether the reported benefit is concrete rather than a generic claim.
- Quantified impact0/250 metrics describe measurable impact.
- Deployment scale10/10Rewards evidence of a live or scaled deployment and meaningful integration scope.
Evidence confidence72%
- Source authority20/25The main evidence is an official vendor-published customer story.
- Claim traceability21/2510 of 12 key fields link to a named source.
- Direct evidence5/201 direct source quote retained.
- Date provenance10/10The publication date comes from the source page or publisher.
- Source transparency8/101 source reference document publisher, URL, authority, retrieval, and supported fields.
- Implementation specificity8/10Rewards source-backed components, data flow, quantified impact, and a specific outcome.
Traceability
Sources & provenance
Field coverage shows which facts each source supports. Dates are shown only when documented by the source.
- https://www.microsoft.com/en/customers/story/1763927195672636703-opap-microsoft-365-gaming-en-greeceMicrosoftFirst-party
Opap customer story
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
- Published on source page May 7, 2024 · Microsoft · First-partyOpen date source
Not separately sourced Industry, Region, Company size. Treat these normalized attributes as lower-confidence until a dedicated source is added.
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