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AI Adoption Impact in Consulting
Reported efficiency gains by using AI-driven workflows.
Primary Sources
AI Is Changing Enterprise Structures At Scale: Anish De, KPMG
Enrich 2025 is centred around reimagining the energy enterprise. What, in your view, is the single biggest disruptor shaping this reimagination?It is AI. Over the last two to three years, AI has progressed rapidly, from generative to agentic AI, and this progression is now collapsing the distance between the front and back of the enterprise. Earlier, there was always a back office supporting the front office. Today, this division is disappearing, and processes are becoming seamless and fully integrated. This is not confined to the energy enterprise alone, but applies to all enterprises. The result is that the future organisation will look structurally different, with talent and technology concentrated in new nerve centres – what used to be called global capability centres. These hubs will now drive efficiency, integration and innovation at scale.That sounds like a structural shift. Will it be a slow evolution or a disruptive change?Traditionally, human-centric changes would take time, but this is moving much faster. We saw during COVID-19 how digital adoption jumped overnight, even though instant messaging tools had existed for years without mass uptake. Something similar is now happening. Enterprises are under enormous margin pressures, and when technology offers them the ability to collapse the front and back and create new capability sets, leaders are pushing hard for change. It is not just about cost arbitrage anymore – it is about accessing entirely new capabilities that disconnected systems did not previously allow. This pressure is accelerating what might otherwise have been a slow evolution.The agenda reflects heightened uncertainty – geopolitics, tech adoption, and sustainability. How are these reshaping strategies for energy companies globally and in India?Despite geopolitical shocks, we are not seeing oil or commodity prices spike as one might expect. This is due to concerns about weak global growth. Inflation is also running higher than in the past, and much of it appears structural. The era of zero-cost money is coming to an end. Combine low growth with cost pressures and sustainability obligations that enterprises cannot ignore, and you have a very difficult environment. At a corporate level, this is not just a discussion topic – it is an existential challenge. Enterprises must meet sustainability targets regardless of political noise, because no one wants to be caught unprepared when political winds shift back. At a corporate level, this is ...
Practical AI Implementation · Enterprise Strategy · International ...
The CEO came back from a conference and said "We need AI. Now." 48 hours later, IT was rolling out Copilot to 2,000 employees. Legal was cc'd on the email. Nobody asked them. Sound familiar? This is happening in manufacturing plants in Germany, financial services firms in Singapore, retail HQs in the UAE, and healthcare organisations across North America — right now — with the same cheerful disregard for what happens when a large language model starts ingesting your most sensitive operational data. Here's the uncomfortable truth nobody in the AI influencer space is telling you: The tools are not the problem. The absence of governance around the tools is. ━━━━━━━━━━━━ I have enormous respect for the voices driving AI adoption. But there is a gap — a significant one — between "just connect your company data to Copilot, it transforms productivity" and the reality of running a business across 12 jurisdictions, subject to GDPR, PDPA, POPIA, CCPA, and an internal data classification policy that took three years to build. Yeah, ChatGPT Enterprise keeps your data private. Yeah, but your Enterprise Agreement doesn't override your local data residency obligations. Yeah, Claude is GDPR-compliant. Yeah, but the tool being compliant and your implementation of it being compliant are two entirely different legal questions. Yeah, you should start fast with a pilot. Yeah, but scale fast into what, exactly? An undocumented data processing arrangement with a third-party AI provider? ━━━━━━━━━━━━ The 6 things that actually go wrong: 1️⃣ Employees paste customer records and contracts into consumer AI tiers, believing "enterprise" covers every legal exposure. It doesn't. 2️⃣ M365 Copilot surfaces everything a user has access to — not just what they should routinely see. Misconfigured permissions become AI-amplified data leaks. 3️⃣ An AI agent drafts a customer communication or influences a hiring decision. The regulator asks: who signed off on that? There is no answer. 4️⃣ Your workflows are built around one vendor's API. Their terms change. A government restricts the service in your operating territory. Your BCP has no chapter for this. 5️⃣ What's lawful under US privacy law may be a breach notification event in South Africa. AI tools are global. Regulations are proudly local. 6️⃣ While IT builds the formal rollout plan, the marketing team has been using the free tier of a consumer AI tool with company data for six months. Shadow IT just got a language ...
S&P Global on Instagram: "To power the AI decisions that matter ...
On June 4, join @profgalloway and leaders from NBCUniversal, PwC, Tech Mahindra, Lumen, and Centene to learn the essential tactics for scaling AI use in 2026.
As global tech giants reallocate billions toward AI infrastructure ...
As global tech giants reallocate billions toward AI infrastructure, workforce strategies ... The Big Four (Deloitte, PwC, EY, KPMG) are not “experimenting” with ...
