Consulting companies’ accelerating adoption of generative AI to automate data work is sending shockwaves throughout the trade, triggering workforce shakeups and layoffs.
This month, PwC reduce roughly 2% of its U.S. workers, roughly 1,500 jobs, in audit and tax traces. EY eradicated 150 roles even because it introduced a $1.4 billion funding to construct an enterprise AI platform. Accenture slashed 19,000 positions (2.5% of its workforce) amid slowing development and rising tech prices in 2023.
McKinsey & Firm is reportedly paying senior workers as much as 9 months’ wage to stop voluntarily, a method trade observers hyperlink to a downturn in consulting spending accelerated by AI-driven change.
KPMG is realigning expertise as AI platforms change components of the audit course of and different routine duties. In November of final 12 months, 333 jobs have been reduce, or roughly 4% of U.S. audit workers.
This escalating wave of AI-driven layoffs is mirrored in IBM CEO Arvind Krishna’s current acknowledgment that IBM has changed a number of hundred routine human assets roles with AI brokers. Krishna’s feedback underscore the unsettling actuality confronting high-performing workers: roles centered round “rote process work” are quickly turning into out of date. Though IBM has reallocated some assets towards roles in software program improvement and gross sales, the underlying message is obvious. Workers 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 data work a lot quicker than anybody, together with the trade’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, lots of the trade’s elite consultants and excessive performers are reinventing themselves shortly earlier than their roles vanish.
Groups within the hardest hit areas usually have dozens of shadow AI apps designed to enhance effectivity and workforce productiveness. Proposal and pitch automation, operations and workflow automation, monetary modeling, situation evaluation, and shopper relationship managers being changed by firm-specific copilots are the place shadow AI prospers. Many are counting on Python-based shadow AI to construct customized automation instruments, bypass inside IT bottlenecks, and ship quicker, differentiated insights that defend their roles in an trade below stress from gen AI.
Python is turning into the language of reinvention
VentureBeat has discovered that lots of the top-tier strategists, entrepreneurs, observe 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 engines like google, Google Gemini 2.5 Professional, Perplexity and different AI platforms’ API keys and calls. Platforms of selection for fine-tuning shadow AI apps embrace 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 collection 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 professional, IT-approved copilots and chatbots. One SME chief confided to VentureBeat that the mixture 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 a whole bunch, of distinctive Google Search Engine APIs and IDs to energy their Python apps. These APIs present exact, real-time integration of exterior knowledge immediately into their shadow AI instruments, additional boosting their analytical edge.
Shadow AI is shortly rising as the brand new consulting stack
An evaluation by Cyberhaven of AI utilization throughout three million workers discovered that 73.8% of office ChatGPT accounts have been private relatively than company, indicating that the majority consultants flip to those instruments independently. Cameron Coles, VP of Advertising and marketing at Cyberhaven’s weblog put up final month, AI Utilization at Work Is Exploding — However 71% of Instruments Put Your Information at Threat, supplies insights into what sort of knowledge is most frequently shared throughout shadow AI apps and the speedy development of the class.
Coles writes, “AI usage at work continues its remarkable growth trajectory. In the past 12 months alone, usage has increased 4.6x, and over the past 24 months, AI usage has grown an astounding 61x. This represents one of the fastest adoption rates for any workplace technology, substantially outpacing even SaaS adoption, which took years to achieve similar penetration levels.”
Inside high consulting companies, the proliferation of self-built, unauthorized apps continues to be explosive. Itamar Golan, CEO of Immediate Safety, 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 lately advised VentureBeat throughout an interview that “many default to indiscriminately training on proprietary data inputs,” exposing companies to substantial threat. Inside knowledge confirms that 70–75% of consultants now usually depend on generative AI apps, immediately attributing productiveness positive aspects 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 grasp the breadth of shadow AI adoption.:
Estimating the true scale of shadow AI in consulting
Whereas most enterprise instruments nonetheless fail to detect the size of shadow AI use, area interviews and telemetry from Immediate Safety, WinWire and interviews with 14 top-tier consulting companies make one factor clear: shadow AI is now 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 govt interviews with CTOs, CISOs, AI leads and companions throughout Tier 1 companies.
Solely actively deployed, production-grade instruments are counted, not one-off prompts, momentary Google Colab notebooks, or ChatGPT browser classes. These numbers replicate a validated decrease certain, doubtless far wanting the true whole.
Shadow AI app panorama in consulting, 2025 (Verified Estimate)
Use Case CategoryEstimated Shadow AI Apps (Q2 2025)Main Instruments UsedPitch & Proposal Automation12,000GPT-4, Gemini, Replit, ColabMarket Segmentation & Targeting9,000Perplexity, Gemini APIs, RAG appsResearch Assistants & Information Bots15,000Claude 3, Gemini Professional, Google Search APIsClient-Going through Chatbots & Agents7,500OpenAI Assistants, LangChain, customized LLMsWorkflow & Productiveness Automation13,000Python automations, Sheets, ZapierFinancial Evaluation & Situation Models18,000Monte Carlo fashions, Gemini + PythonTotal (Validated Estimate)74,500+
Sources: Immediate Safety, WinWire, Cyberhaven, VentureBeat interviews with 14 international companies
Shadow AI development trajectory: What comes subsequent
Shadow AI is scaling quicker than any sanctioned inside platform, and most companies haven’t any actual strategy to sluggish it down. Based mostly on a conservative 5% month-over-month development fee, the variety of actively used shadow apps may greater than double by mid-2026.
What began as remoted productiveness scripts has advanced into one thing extra sturdy. Shadow AI is now not a fringe toolset. It’s now a parallel supply stack. It operates exterior IT, with out formal governance, but it powers lots of the high-value outputs companies ship to shoppers on daily basis.
Projected shadow AI app development in consulting
QuarterProjected App CountDrivers of GrowthQ2 202574,500+Verified energetic apps from Immediate Safety, WinWire, and interviewsQ3 202590,000 to 95,000Growth in Gemini and Claude apps, partner-led developmentQ4 2025110,000 to 115,000Shadow instruments grow to be embedded in shopper supply workflowsQ1 2026130,000 to 140,000Emergence of gray-market copilots and self-maintained appsQ2 2026150,000 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 replicate persistent apps and workflows constructed utilizing APIs, scripting, or automated brokers developed inside consulting groups.
The best way to strategically handle shadow AI dangers
Shadow AI is flourishing as a result of conventional IT and cybersecurity frameworks aren’t designed to trace its use. IT and safety groups in almost each enterprise VentureBeat spoke with have three to 5 instances the variety of tasks they will full this 12 months. Whereas getting a brand new copilot out is a excessive precedence, it may face useful resource and approval hurdles consequently.
Arora underscores that “most traditional management tools lack comprehensive visibility into AI apps,” enabling unauthorized AI to quietly embed itself inside enterprise workflows.” Arora’s insights reveal an underlying fact: Workers aren’t performing maliciously; they’re scared of being let go whereas concurrently overwhelmed with work, leveraging AI to deal with escalating workloads, shrinking deadlines, and relentless efficiency expectations.
Moderately than stifling AI adoption, Arora advocates proactive empowerment by means of strategic, centralized governance. By institutionalizing clear oversight, organizations can harness AI securely, reworking shadow AI from an unseen risk 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 current interview with VentureBeat, explicitly designed for enterprises navigating the complexities of shadow AI:
Shadow AI audits are desk stakes:Repeatedly take stock of all unauthorized AI exercise by means 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 preserve an accepted AI instruments catalog accessible to all groups.
Get AI-aware safety controls in place instantly:Deploy specialised Information 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 stop 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 prompt Python apps, fine-tuned to shopper wants.
GRC integration and steady coaching:Combine AI governance inside current governance, threat, and compliance (GRC) frameworks, and persistently seek the advice of on safe, compliant AI practices.
Keep away from blanket bans, it’s gas for much more shadow AI app improvement:Acknowledge that outright AI bans inevitably backfire, growing shadow AI proliferation. As an alternative, 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 are 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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