DEWA Moves from Pilot to Platform with Microsoft Copilot and Power Platform

Dubai Electricity and Water Authority (DEWA) has moved from pilot to platform: the utility announced a formal adoption and wider rollout of Microsoft Power Platform and Microsoft Copilot, embedding generative AI across customer-facing channels and developer workflows as part of a broad digital‑transformation push.

Background / Overview​

DEWA’s AI journey is long-running and now accelerating. The authority began experimenting with AI as early as 2017 and introduced the ChatGPT-backed virtual assistant “Rammas” into customer channels in 2023; the pilot phase delivered rapid, measurable customer benefits — tens of thousands of chatbot interactions and very high customer satisfaction scores — which helped make the case for a broader generative‑AI strategy.
By early 2025 DEWA’s statements and industry reporting show the organisation expanding its use of generative AI to include Microsoft Copilot across the Power Platform and Microsoft 365 ecosystems, with plans to apply Copilot-driven assistants and developer aids across operations, SAP integration, security tooling and multiple “Rammas” variants for consumers and staff.
This piece examines what DEWA is doing, why it matters for utilities and public‑sector IT, the capabilities Microsoft’s Copilot family brings to low‑code and developer workflows, and the governance, security and operational risks organisations must manage when rolling generative AI into mission‑critical services.

---

What DEWA announced and why it matters​

The announcement in plain terms​

• DEWA has adopted Microsoft Power Platform (Power Apps, Power Automate, Dataverse, Copilot Studio/agents) and Microsoft Copilot to accelerate application development, automate back‑office tasks and augment its virtual employee, Rammas.
• DEWA reported earlier success with ChatGPT in its Rammas pilot: during the initial ChatGPT pilot phase Rammas handled more than 32,000 queries with around 90% customer happiness, and later reporting shows Rammas responding to many more inquiries as the service matured.
• The utility intends to use Copilot to help developers write code, generate Power Fx formulas, create Power Apps and accelerate the delivery of digital services across customer, employee and operational channels. Microsoft’s Power Platform Copilot features are specifically designed to speed low‑code creation and assist both makers and pro developers.

Why this is material for utilities and government IT​

Utilities are complex, regulated, and data‑intensive: they run ERP systems, asset management, SCADA/OT environments, and customer billing at scale. Embedding generative AI into the layers that touch customers and developers can yield:

• Faster application delivery for new digital services (forms, alerts, self‑service)
• Reduced time for routine coding and formula generation (Power Fx, connectors)
• Enhanced chatbot capability and multilingual support for customer channels
• New productivity gains in knowledge work (summaries, meeting recaps, incident triage)

DEWA’s move is notable because it is a large public utility using the same Microsoft enterprise Copilot tooling many organisations are evaluating, which makes DEWA a useful early case study for the sector.

---

What Microsoft Copilot and Power Platform actually do for developers and makers​

Copilot for low‑code (Power Platform) — what to expect​

Microsoft has layered Copilot functionality across Power Apps, Power Automate and Copilot Studio so that makers and developers can:

• Create apps from natural‑language prompts and data (Dataverse, Excel). Copilot can scaffold tables, screens and simple business logic from a description of the intended app.
• Generate and explain Power Fx formulas and suggest fields or bindings based on data schema — helpful for onboarding and troubleshooting.
• Use Copilot Studio and agent‑based workflows to author reusable “Copilot agents” that automate common actions and integrate with Microsoft Graph, SharePoint, SAP and external APIs.

These features are not theoretical: Microsoft documents and product updates show Copilot features moving into general availability and public preview across Power Platform since late 2023 and through 2024–2025.

Copilot for code and enterprise productivity​

For software developers and technical teams, Copilot’s ecosystem includes:

• GitHub Copilot variants (developer coding assistance) and Power Platform Copilot features that can propose formulas, connectors, and pipeline notes.
• Microsoft 365 Copilot (Word, Excel, PowerPoint, Outlook, Teams) which brings AI summaries, drafting and data analysis into everyday tasks.
• Copilot Studio for building and governing agents, plus admin controls to manage lifecycle, permissions and DLP.

Microsoft’s product messaging positions Copilot as a productivity layer that must be grounded in tenant data (Microsoft Graph, Dataverse) and governed through enterprise controls — a design intended to make Copilot “enterprise‑ready.”

---

Strengths and immediate benefits​

• Speed of delivery: Copilot can drastically shorten prototyping cycles (idea → working prototype) in Power Apps and reduce formula‑writing time. This directly supports DEWA’s “Digital DEWA” ambitions to accelerate service rollouts.
• Improved customer automation: Augmented chatbots like Rammas can deliver faster, multilingual, and context‑aware answers. DEWA’s pre‑Copilot ChatGPT pilot already demonstrated significant customer happiness gains; Copilot’s tighter integration with Microsoft 365 and Dataverse promises deeper grounding in enterprise data.
• Democratization of development: Low‑code makers and citizen developers can build more capable apps with less hand‑coding thanks to Copilot suggestions and Copilot Studio agents. This can ease IT backlog pressures in large organisations.
• Operational efficiency: Copilot’s ability to summarize documents, analyze Excel data and draft communications saves knowledge‑worker time across the enterprise — a repeatable productivity win when scaled.

---

Important caveats and risks DEWA (and any organisation) must manage​

No single paragraph can fully neutralise the operational and governance work required to embed generative AI safely. The most significant areas to address are:

1. Data residency, sovereignty and regulatory compliance​

Generative AI prompts and responses may contain or be derived from sensitive enterprise content. For regulated public bodies, the jurisdiction where interaction data is processed matters.

• Microsoft has signalled product‑level options for in‑country or region‑aware processing of Copilot interactions in certain countries (UAE in‑country options are part of Microsoft’s regional commitments). Organisations should confirm whether the Copilot components they plan to use process prompts or logs outside the country, and whether contractual residency guarantees or technical controls (local Azure regions, ExpressRoute, confidential compute) are available and sufficient for compliance.

2. Hallucination and factual accuracy​

Generative models can produce plausible but incorrect outputs — a critical issue when answers feed customer guidance, billing, or operational decisions.

• Mitigations: enforce retrieval‑grounded workflows (Copilot that cites tenant data), require human review for high‑impact outputs, and instrument automated checks to flag divergent or unverifiable responses. Microsoft positions Copilot as “work‑grounded” using Microsoft Graph and tenant data, but the practical quality depends on indexing, prompt design and testing.

3. Data leakage and IP concerns​

Copilot suggestions may be influenced by the model’s training data or by cross‑tenant telemetry unless controls prevent it.

• Mitigations: apply Data Loss Prevention (DLP) policies, Purview sensitivity labels, restrict connectors, and use tenant‑level controls and Copilot admin settings to block or limit access to sensitive sources. Microsoft’s governance features in Power Platform and Copilot Studio are explicit about these controls, but they must be configured proactively.

4. Vendor lock‑in and architectural coupling​

Embedding Copilot deeply into Dataverse, Microsoft 365 and Power Platform creates powerful integrations but increases coupling to Microsoft’s cloud ecosystem.

• Mitigations: design modular integrations (clear APIs and data export paths), negotiate contractual terms for portability, and maintain critical datasets in vendor‑neutral formats where feasible.

5. Operational security and supply‑chain risk​

Agents that can act (Copilot Actions) or modify systems increase the attack surface. Misconfigured connectors or overly permissive agents could be abused.

• Mitigations: enforce least privilege for agents and connectors, require change control and code review for agent logic, and include agents in standard incident‑response playbooks with audit trails and revocation capability.

---

Practical rollout checklist (a pragmatic sequence for DEWA‑style organisations)​

• Align governance and legal teams on permitted Copilot use cases and a data residency policy.
• Start small with narrow, measurable pilots: customer chatbot intents, internal HR/IT self‑service agents, or a single Power Apps scenario.
• Configure tenant grounding: ensure Copilot agents are connected only to approved Dataverse/SharePoint sources and that outputs are audited.
• Apply DLP and sensitivity labels; block risky connectors by default.
• Enforce human‑in‑the‑loop for high‑risk outputs (metering, billing, asset control, OT commands).
• Run red‑team testing on agents and Copilot Actions to uncover abuse paths.
• Train employees and makers on prompt engineering, model behaviours, and escalation processes.
• Measure impact: track time saved, defect rates, customer satisfaction, and compliance incidents — use those metrics to expand or roll back capabilities.

---

Governance, auditing and the role of Copilot admin tools​

Microsoft’s product set includes admin tooling and guidance intended to make Copilot adoption auditable and controllable:

• Copilot Hub / Admin center: consolidated visibility into Copilot usage, costs and feature rollout.
• Copilot Studio: low‑code/pro‑code authoring with templates, lifecycle controls and risk classification for agents; intended admin‑level guardrails for enterprise publishing.
• DLP / Purview / Entra integration: standard Microsoft controls that map to data classification, audit logging and identity policies. Teams must operationalise these tools as part of the rollout rather than treating them as optional extras.

These controls are meaningful, but they do not remove operational responsibility: organisations still must maintain a program of agent review, incident readiness and continuous model‑output validation.

---

What remains uncertain or needs validation in public reporting​

• Claims that DEWA was the first utility globally to adopt Microsoft Copilot are reported in industry coverage but are difficult to independently verify across every utility worldwide; treat absolute “first” claims as part of PR framing unless formally certified.
• The exact in‑country processing and residency guarantees for Copilot interactions in the UAE (availability windows and eligibility criteria) are evolving; Microsoft’s regional product options and timelines are advancing but may include eligibility restrictions and phased service launches that require legal review. Organisations should obtain precise contractual language and a day‑one service catalogue before procurement.

---

Why DEWA’s approach is instructive — and what other utilities can learn​

DEWA’s path reads like a modern, pragmatic adoption playbook: trial disruptive tools (ChatGPT in Rammas), measure real user outcomes (customer happiness, query volumes), then extend to production with enterprise tooling (Power Platform and Copilot) while emphasising governance and capacity building.
Key takeaways for other utilities:

• Validate generative AI with measurable KPIs before broadly deploying it in customer channels.
• Use agent‑based, low‑risk pilots to get comfortable with lifecycle operations, then expand into higher‑value back‑office automation.
• Prioritise compliance, data residency and DLP early — they are not “nice to have” controls at scale.
• Balance productivity gains against the cost and complexity of governance: Copilot licensing, admin effort, and security posture all matter.

---

Conclusion​

DEWA’s decision to embed Microsoft Copilot and the Power Platform across its services is a clear signal that generative AI has moved from experimentation to operationalisation in large public utilities. The potential upsides are substantial: faster development cycles, better customer automation, and productivity gains for knowledge workers. The hard work, however, lies in secure, compliant implementation — enforcing data residency, preventing leakage, validating outputs, and building governance that keeps AI as a tool rather than an ungoverned actor.
For organisations watching DEWA, the essential lesson is pragmatic: let measurable pilots drive the expansion, insist on technical and contractual clarity around where and how prompts and logs are processed, and make governance and human oversight core to the program. DEWA’s rollout is a leading indicator for utilities globally — it shows what is possible, but also highlights the operational diligence required to make generative AI a reliable, trustworthy part of essential public services.

---

Source: Enlit World DEWA adopts MS Copilot