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Consulting companies’ accelerating adoption of generative AI to automate information work is sending shockwaves throughout the {industry}, triggering workforce shakeups and layoffs.
This month, PwC lower roughly 2% of its U.S. workers, approximately 1,500 jobs, in audit and tax strains. EY eliminated 150 roles even because it introduced a $1.4 billion investment to construct an enterprise AI platform. Accenture slashed 19,000 positions (2.5% of its workforce) amid slowing progress and rising tech prices in 2023.
McKinsey & Company is reportedly paying senior workers as much as nine months’ salary to quit voluntarily, a technique {industry} observers hyperlink to a downturn in consulting spending accelerated by AI-driven change.
KPMG is realigning expertise as AI platforms change elements of the audit course of and different routine duties. In November of final 12 months, 333 jobs have been lower, or roughly 4% of U.S. audit workers.
This escalating wave of AI-driven layoffs is mirrored in IBM CEO Arvind Krishna’s recent acknowledgment that IBM has changed a number of hundred routine human sources roles with AI brokers. Krishna’s feedback underscore the unsettling actuality confronting high-performing workers: roles centered round “rote course of work” are quickly turning into out of date. Though IBM has reallocated some resources toward roles in software development and sales, the underlying message is evident. Staff more and more understand AI brokers as existential threats, fueling anxiousness and driving many to construct shadow AI apps to protect their relevance defensively.
The underside line is that gen AI is redefining all types of information work a lot sooner than anybody, together with the {industry}’s elite consultants, leaders and companions, anticipated.
AI layoffs are sparking a survival mindset
Fearing they could be caught up in sweeping layoffs pushed by AI and automation, most of the {industry}’s elite consultants and excessive performers are reinventing themselves rapidly earlier than their roles vanish.
Groups within the hardest hit areas usually have dozens of shadow AI apps designed to enhance effectivity and group productiveness. Proposal and pitch automation, operations and workflow automation, monetary modeling, state of affairs evaluation, and shopper relationship managers being changed by firm-specific copilots are the place shadow AI thrives. Many are counting on Python-based shadow AI to construct customized automation instruments, bypass inside IT bottlenecks, and ship sooner, differentiated insights that defend their roles in an {industry} underneath strain from gen AI.
Python is turning into the language of reinvention
VentureBeat has discovered that most of the top-tier strategists, entrepreneurs, practice leaders and their groups have gotten proficient in creating Python-based apps that may take evaluation and insights past the prevailing genAI instruments supplied by IT. Groups creating these apps are proficient with Open AI, Google programmable search engines, Google Gemini 2.5 Pro, Perplexity and different AI platforms’ API keys and calls. Platforms of selection for fine-tuning shadow AI apps embody Google Colab and Google AI Studio. Many are utilizing Replit to create standalone apps.
Constructing Shadow AI apps with enterprise-grade attain
By combining a sequence of APIs and search engine IDs from Anthropic, Perplexity, Open AI and Google, the pace, accuracy and acuity of insights, associates’ shadow AI apps ship attain past the present scope of legit, IT-approved copilots and chatbots. One SME chief confided to VentureBeat that the mix of APIs and Python fine-tuning makes it doable to create apps so hyper-customized to a shopper’s objectives that it’s saving him days of handbook work aggregating and analyzing knowledge.
Associates at high companies globally have created dozens, and in some circumstances tons of, of distinctive Google Search Engine APIs and IDs to energy their Python apps. These APIs present exact, real-time integration of exterior knowledge straight into their shadow AI instruments, additional boosting their analytical edge.
Shadow AI is rapidly rising as the brand new consulting stack
An analysis by Cyberhaven of AI utilization throughout three million workers discovered that 73.8% of office ChatGPT accounts have been private somewhat than company, indicating that almost all consultants flip to those instruments independently. Cameron Coles, VP of Advertising and marketing at Cyberhaven’s weblog put up final month, AI Usage at Work Is Exploding — But 71% of Tools Put Your Data at Risk, supplies insights into what sort of knowledge is most frequently shared throughout shadow AI apps and the speedy progress of the class.
Coles writes, “AI utilization at work continues its outstanding progress trajectory. Previously 12 months alone, utilization has elevated 4.6x, and over the previous 24 months, AI utilization has grown an astounding 61x. This represents one of many quickest adoption charges for any office know-how, considerably outpacing even SaaS adoption, which took years to attain comparable penetration ranges.”
Inside high consulting companies, the proliferation of self-built, unauthorized apps continues to be explosive. Itamar Golan, CEO of Prompt Security, notes, “We see 50 new AI apps a day, and we’ve already cataloged over 12,000,” highlighting how quickly these shadow instruments are rising. He just lately instructed VentureBeat throughout an interview that “many default to indiscriminately coaching on proprietary knowledge inputs,” exposing companies to substantial threat. Inner knowledge confirms that 70–75% of consultants now regularly rely on generative AI apps, straight attributing productiveness positive factors to shadow AI apps. It’s grow to be the weapon of selection for consulting’s high expertise, enabling them to provide distinctive work in a fraction of the time.
VentureBeat interviewed Golan, Vineet Arora, CTO of WinWire, and senior leaders at fourteen main international consultancies to know the breadth of shadow AI adoption.:
Estimating the true scale of shadow AI in consulting
Whereas most enterprise instruments nonetheless fail to detect the dimensions of shadow AI use, discipline interviews and telemetry from Immediate Safety, WinWire and interviews with 14 top-tier consulting companies make one factor clear: shadow AI is not a fringe phenomenon. It’s rising as a parallel tech stack constructed from the bottom up by consultants themselves.
VentureBeat’s estimate incorporates:
- Immediate Safety telemetry, which detects ~50 new shadow AI apps per day and has already cataloged 12,000+ instruments throughout consulting companies globally.
- WinWire enterprise AI knowledge, overlaying Gemini, GPT-4, Claude 3 and Colab-based deployments.
- Cyberhaven utilization knowledge, which reveals that 73.8% of ChatGPT office accounts are unauthorized, and enterprise AI utilization has grown 61x in 24 months.
- 14 government interviews with CTOs, CISOs, AI leads and companions throughout Tier 1 companies.
Solely actively deployed, production-grade instruments are counted, not one-off prompts, non permanent Google Colab notebooks, or ChatGPT browser classes. These numbers mirror a validated decrease sure, probably far in need of the true complete.
Shadow AI app panorama in consulting, 2025 (Verified Estimate)
| Use Case Class | Estimated Shadow AI Apps (Q2 2025) | Major Instruments Used |
| Pitch & Proposal Automation | 12,000 | GPT-4, Gemini, Replit, Colab |
| Market Segmentation & Concentrating on | 9,000 | Perplexity, Gemini APIs, RAG apps |
| Analysis Assistants & Information Bots | 15,000 | Claude 3, Gemini Professional, Google Search APIs |
| Shopper-Dealing with Chatbots & Brokers | 7,500 | OpenAI Assistants, LangChain, customized LLMs |
| Workflow & Productiveness Automation | 13,000 | Python automations, Sheets, Zapier |
| Monetary Evaluation & Situation Fashions | 18,000 | Monte Carlo fashions, Gemini + Python |
| Complete (Validated Estimate) | 74,500+ |
Sources: Immediate Safety, WinWire, Cyberhaven, VentureBeat interviews with 14 international companies
Shadow AI progress trajectory: What comes subsequent
Shadow AI is scaling sooner than any sanctioned inside platform, and most companies haven’t any actual technique to sluggish it down. Based mostly on a conservative 5% month-over-month progress fee, the variety of actively used shadow apps might greater than double by mid-2026.
What began as remoted productiveness scripts has advanced into one thing extra sturdy. Shadow AI is not a fringe toolset. It’s now a parallel supply stack. It operates exterior IT, with out formal governance, but it powers most of the high-value outputs companies ship to shoppers every single day.
Projected shadow AI app progress in consulting
| Quarter | Projected App Depend | Drivers of Development |
|---|---|---|
| Q2 2025 | 74,500+ | Verified energetic apps from Immediate Safety, WinWire, and interviews |
| Q3 2025 | 90,000 to 95,000 | Development in Gemini and Claude apps, partner-led improvement |
| This autumn 2025 | 110,000 to 115,000 | Shadow instruments grow to be embedded in shopper supply workflows |
| Q1 2026 | 130,000 to 140,000 | Emergence of gray-market copilots and self-maintained apps |
| Q2 2026 | 150,000 to 160,000+ | Shadow AI evolves into an ungoverned parallel supply stack |
These projections exclude one-off use of ChatGPT or Gemini in browser classes. They mirror persistent apps and workflows constructed utilizing APIs, scripting, or automated brokers developed inside consulting groups.
The way to strategically handle shadow AI dangers
Shadow AI is prospering as a result of conventional IT and cybersecurity frameworks aren’t designed to trace its use. IT and safety groups in practically each enterprise VentureBeat spoke with have three to 5 occasions the variety of initiatives they’ll full this 12 months. Whereas getting a brand new copilot out is a excessive precedence, it may well face useful resource and approval hurdles consequently.
Arora underscores that “most conventional administration instruments lack complete visibility into AI apps,” enabling unauthorized AI to quietly embed itself inside enterprise workflows.” Arora’s insights reveal an underlying fact: Staff aren’t appearing maliciously; they’re afraid of being let go whereas concurrently overwhelmed with work, leveraging AI to deal with escalating workloads, shrinking deadlines, and relentless efficiency expectations.
Relatively than stifling AI adoption, Arora advocates proactive empowerment by way of strategic, centralized governance. By institutionalizing clear oversight, organizations can harness AI securely, remodeling shadow AI from an unseen menace right into a managed asset.
A blueprint for governance
Consultancies’ senior administration groups want a transparent, sensible roadmap to get in entrance of shadow AI dangers and harness its strategic potential. Arora outlined an in depth governance framework throughout a latest interview with VentureBeat, explicitly designed for enterprises navigating the complexities of shadow AI:
- Shadow AI audits are desk stakes:
Recurrently take stock of all unauthorized AI exercise by way of sturdy community monitoring and detailed software program asset administration.
- Create an Workplace of Accountable AI:
Centralize AI governance features spanning coverage creation, vendor assessments and threat evaluation, and keep an accepted AI instruments catalog accessible to all groups.
- Get AI-aware safety controls in place instantly:
Deploy specialised Knowledge Loss Prevention (DLP) instruments and real-time inference monitoring able to detecting delicate knowledge leaks particular to AI functions in real-time.
- Go all in on making use of zero belief to AI architectures:
Undertake strict output validation protocols, anonymize or tokenize delicate inputs, and rigorously handle knowledge flows to attenuate publicity and forestall unauthorized knowledge coaching.
- Discover out the place the roadblocks are to getting extra gen AI instruments out now:
Each group can enhance on the pace at which it deploys new applied sciences. Discover out the place the gaps and roadblocks are holding the consultancy again from delivering more proficient copilots and chatbots. It’s important to get a roadmap outlined for IT and DevOps to work on for internally advised Python apps, fine-tuned to shopper wants.
- GRC integration and steady coaching:
Combine AI governance inside current governance, threat, and compliance (GRC) frameworks, and constantly seek the advice of on safe, compliant AI practices.
- Keep away from blanket bans, it’s gasoline for much more shadow AI app improvement:
Acknowledge that outright AI bans inevitably backfire, growing shadow AI proliferation. As a substitute, quickly deploy safe, sanctioned alternate options that allow compliant, productive innovation.
Initially an underground productiveness hack, shadow AI has emerged as a decisive think about how top-tier consultants ship differentiated shopper worth. Pushed by a stark survival crucial amid widespread AI-triggered layoffs, elite expertise now depends on Python-driven, generative AI-powered options, enabling uniquely tailor-made shopper insights and speedy responses to their shoppers.
Consulting companies which can be sluggish to adapt or hesitant to strategically harness these improvements strategically threat forfeiting their future aggressive edge. The trail ahead calls for not prohibition however considerate, safe integration of shadow AI and the transformation of potential dangers into decisive strategic benefits.
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