AI Research
2025 State of AI Cost Management Research Finds 85% of Companies Miss AI Forecasts by >10%
Despite rapid adoption, most enterprises lack visibility, forecasting accuracy, and margin control around AI investments. Hidden infrastructure costs are eroding enterprise profitability, according to newly published survey data.
AUSTIN, Texas, Sept. 10, 2025 /PRNewswire/ — As enterprises accelerate investments in AI infrastructure, a new report reveals a troubling financial reality: most organizations can’t forecast what they’re spending, or control how AI costs impact margins. According to the 2025 State of AI Cost Management, 80% of enterprises miss their AI infrastructure forecasts by more than 25%, and 84% report significant gross margin erosion tied to AI workloads.
The report, published by Benchmarkit in partnership with cost governance platform Mavvrik, reveals how AI adoption, across large language models (LLMs), GPU-based compute, and AI-native services, is outpacing cost governance. Most companies lack the visibility, attribution, and forecasting precision to understand where costs come from or how they affect margins.
“These numbers should rattle every finance leader. AI is no longer just experimental – it’s hitting gross margins, and most companies can’t even predict the impact,” said Ray Rike, CEO of Benchmarkit. “Without financial governance, you’re not scaling AI. You’re gambling with profitability.”
Top Findings from the 2025 State of AI Cost Management Report include:
AI costs are crushing enterprise margins
- 84% of companies see 6%+ gross margin erosion due to AI infrastructure costs
- 26% report margin impact of 16% or higher
The great AI repatriation has begun
- 67% are actively planning to repatriate AI workloads; another 19% are evaluating
- 61% already run hybrid AI infrastructure (public + private)
- Only 35% include on-prem AI costs in reporting, leaving major blind spots
Hidden cost surprises come from unexpected places
- Data platforms top source of unexpected AI spend (56%); LLMs rank 5th
- Network access costs is the second-largest cost surprise (52%)
AI forecasting is fundamentally broken
- 80% miss AI forecasts by 25%+
- 24% are off by 50% or more
- Only 15% forecast AI costs within 10% margin of error
Visibility gaps are stalling governance
- Lack of visibility is the #1 challenge in managing AI infrastructure costs
- 94% say they track costs, but only 34% have mature cost management
- Companies charging for AI show 2x greater cost maturity in attribution and cost discipline
Access the full report: The full report details how automation, cost attribution methods, and cloud repatriation strategies factor into AI cost discipline. To view the analysis, please visit: https://www.mavvrik.ai/state-of-ai-cost-governance-report/
“AI is blowing up the assumptions baked into budgets. What used to be predictable, is now elastic and expensive,” said Sundeep Goel, CEO of Mavvrik. “This shift doesn’t just affect IT, it’s reshaping cost models, margin structures, and how companies scale. Enterprises are racing to build with AI, but when most can’t explain the bill, it’s no longer innovation, it’s risk.”
Why It Matters
AI isn’t just a technology challenge, it’s a financial one. From LLM APIs to GPU usage and data movement, infrastructure costs are scaling faster than most companies can track them. Without clear attribution across cloud and on-prem environments, leaders are making pricing, packaging, and investment decisions in the dark.
With AI spend becoming a significant line in COGS and gross margin targets under pressure, CFOs should be sounding the alarm. Yet most finance teams haven’t prioritized governance.
About the State of AI Cost Management
The 2025 State of AI Cost Management report is based on survey results from 372 enterprise organizations across diverse industries and revenue tiers. It measures cost governance maturity, spanning forecast accuracy, infrastructure mix (cloud vs. on–prem), attribution capability, and gross margin impact. https://www.mavvrik.ai/.
About Mavvrik
Mavvrik is the financial control center for modern IT. By embedding financial governance at the source of every cost signal, Mavvrik provides enterprises with complete visibility and control across cloud, AI, SaaS, and on-prem infrastructure. Built for CFOs, FinOps, and IT leaders, Mavvrik eliminates financial blind spots and transforms IT costs into strategic investments. With real-time cost tracking, automated chargebacks, and predictive budget controls, Mavvrik helps enterprises reduce waste, govern AI and hybrid cloud spend, and maintain financial precision at scale. Visit www.mavvrik.ai to learn more.
Media Contact:
Rick Medeiros
510-556-8517
[email protected]
SOURCE Mavvrik
AI Research
$3.1 Million Raised To Advance Autonomous Investment Research Platform

Pascal AI Labs, a rapidly growing technology company focused on transforming how investment research is conducted, has announced the close of a $3.1 million seed funding round. The funding was led by Kalaari Capital, with additional participation from Norwest, Infoedge Ventures, Antler, and several prominent angel investors.
This funding marks a significant step in the company’s journey to bring advanced, AI-driven research capabilities to financial institutions worldwide.
The new capital will be used to speed up the development of Pascal AI’s autonomous investment workflows, expand its presence in the United States, and form strategic partnerships with key data providers.
The company’s platform is already in use by more than 25 financial firms across the U.S. and the Asia-Pacific region, including private equity funds managing $2 billion in assets and one of the world’s top three asset managers with over $1 trillion under management.
Pascal AI offers secure and native connections to data on over 16,000 publicly traded companies across 27 markets, giving investment teams a broad and reliable foundation for their work.
The problem that Pascal AI is addressing is one that many investment professionals are familiar with. Analysts and portfolio managers are inundated with vast amounts of data from company filings, earnings call transcripts, market reports, and internal research notes.
While existing platforms can surface this information, they often fail to capture the accumulated judgment and institutional knowledge that experienced investors rely on. As a result, analysts spend hours manually piecing together information, and chief investment officers often lack a clear, forward-looking view of their portfolios.
Pascal AI takes a different approach by automating the entire investment lifecycle. The platform learns from a firm’s proprietary history—its past decisions, research notes, and investment patterns so it can reason and act like a seasoned investor rather than simply retrieving data. This means it can proactively connect insights, identify risks, and suggest actions in a way that reflects the unique thinking of each firm.
Because the stakes in investment decision-making are high, trust and security are central to Pascal AI’s design. The platform is built on a proprietary Knowledge Graph that makes every action fully auditable and traceable. It supports enterprise-grade security features, including role-based permissions and the option for on-premise deployment, ensuring that sensitive information remains protected while still enabling robust AI-driven analysis.
Pascal AI was founded by Vibhav Viswanathan and Mithun Madhusudan, both of whom bring deep expertise in finance, artificial intelligence, and scaling technology products.
Viswanathan, a graduate of the University of Chicago Booth School of Business, previously led AWS Inferentia and Neuron in Silicon Valley and has hands-on investment experience from his time at Capital Group and NEA-IUVP.
Madhusudan, an alumnus of the Indian Institute of Management Bangalore, has led AI and product teams at Indian tech unicorns Apna and ShareChat, where he helped scale AI products to more than 100 million users.
KEY QUOTES:
“The future of investment management is autonomous investment research. Pascal AI is systematically automating complex investment workflows with the long-term vision of creating a fully autonomous investment research company. This funding allows us to accelerate that journey, moving from workflow automation to true autonomy, and giving analysts instant, auditable insights and CIOs a continuously updated view of exposures and performance”.
Vibhav Viswanathan, co-founder and CEO of Pascal AI
“At Kalaari, we believe the next decade will see a decisive shift toward autonomous research platforms that can scale human judgment with machine intelligence. Pascal AI is at the forefront of this transformation—building secure, auditable, and truly agentic workflows that don’t just process information, but reason like an investor. What stood out to us was the clarity and conviction with which Vibhav and Mithun are reimagining how investors and CIOs make decisions. With strong early traction from marquee global clients, the team has already validated the depth of the problem and the strength of their solution. We are excited to partner with them on this mission.”
Kalaari Capital Partner Sampath P
AI Research
Chair File: Using Innovation and AI to Advance Health

With all of the challenges facing health care — a shrinking workforce population, reduced funding, new technologies and pharmaceuticals — it’s no longer an option to change, but an imperative. In order to keep caring for our communities well into the future, we need to transform how we provide care to people. Technology, artificial intelligence and digital transformation can not only help us mitigate these trends but truly innovate and find new ways of making health better.
There are many exciting capabilities already making their way into our field. Ambient listening technology for providers and other automation and AI reduce administrative burden and free up people and resources to improve front-line care. Within the next five years, we expect hospital “smart rooms” to be the norm; they leverage cameras and AI-assisted alerting to improve safety, enable virtual care models across our footprint and allow us to boost efficiency while also improving quality and outcomes.
It’s easy to get caught up in shiny new tools or cutting-edge treatments, but often the most impactful innovations are smaller — adapting or designing our systems and processes to empower our teams to do what they do best.
That’s exactly what a new collaboration with the AHA and Epic is aiming to do. A set of point-of-care tools in the electronic health record is helping providers prevent, detect and treat postpartum hemorrhage, which is responsible for 11% of maternal deaths in the U.S. Early detection and treatment of PPH is key to a full recovery. One small innovation — incorporating tools into your EHR and labor and delivery workflows — is having a big impact: enhancing providers’ ability to effectively diagnose and treat PPH.
It’s critical to leverage technology advancements like this to navigate today’s challenging environment and advance health care into the future. However, at the same time, we also need to focus on how these opportunities can deliver measurable value to our patients, members and the communities we serve.
I will be speaking with Jackie Gerhart, M.D., chief medical officer at Epic, later this month for a Leadership Dialogue conversation. Listen in to learn more about how AI and other technological innovations can better serve patients and make actions more efficient for care providers.
Helping You Help Communities – Key AHA Resources
AI Research
Malware that uses artificial intelligence to bypass security

Redazione RHC : 15 September 2025 19:44
A new EvilAI malware campaign tracked by Trend Micro has demonstrated how artificial intelligence is increasingly becoming a tool for cybercriminals. In recent weeks, dozens of infections have been reported worldwide, with the malware masquerading as legitimate AI-powered apps and displaying professional-looking interfaces, functional features, and even valid digital signatures. This approach allows it to bypass the security of both corporate systems and home devices.
Country | Count |
India | 74 |
United States | 68 |
France | 58 |
Italy | 31 |
Brazil | 26 |
Germany | 23 |
United Kingdom | 14 |
Norway | 10 |
Spain | 10 |
Canada | 8 |
analysts began monitoring the threat on August 29 and within a week had already noticed a wave of large-scale attacks. The largest number of cases was detected in Europe (56), followed by the Americas and AMEA regions (29 each). By country, India leads with 74 incidents, followed by the United States with 68 and France with 58. The list of victims also included Italy, Brazil, Germany, Great Britain, Norway, Spain, and Canada.
The most affected sectors are manufacturing, public, medical, technology, and retail. The spread was particularly severe in the manufacturing sector, with 58 cases, and in the public and healthcare sectors, with 51 and 48 cases, respectively.
EvilAI is distributed via newly registered fake domains, malicious advertisements, and forum links. The installers use neutral but plausible names like App Suite, PDF Editor, or JustAskJacky, which reduces suspicion.
Once launched, these apps offer real functionality, from document processing to recipes to AI-powered chat, but they also incorporate a hidden Node.js loader. It injects obfuscated JavaScript code with a unique identifier into the Temp folder and executes it via a minimized node.exe process.
Persistence on the system occurs in several ways simultaneously: a Windows scheduler task is created in the form of a system component named sys_component_health_{UID}, a Start menu shortcut and an autoload key are added to the registry. The task is triggered every four hours, and the registry ensures it’s activated on login.
This multi-layered approach makes threat removal particularly laborious. All code is built using language models, which allow for a clean, modular structure and bypasses static signature analyzers. Complex obfuscation provides additional protection: control flow alignment with MurmurHash3-based loops and Unicode-encoded strings.
To steal data, EvilAI uses Windows Management Instrumentation and registry queries to identify active Chrome and Edge processes. These are then forcibly terminated to unlock the credential files. The “Web Data” and “Preferences” browser settings are copied with the Sync suffix to the original profile directories and then stolen via HTTPS POST requests.
The communication channel with the command and control server is encrypted using the AES-256-CBC algorithm with a key generated based on the unique infection ID. Infected machines regularly query the server, receiving commands to download additional modules, modify registry parameters, or launch remote processes.
Experts advise organizations to rely not only on digital signatures and application appearance, but also to check distribution sources and pay particular attention to programs from new publishers. Behavioral mechanisms that record unexpected Node.js launches, suspicious scheduler activity, or startup entries can provide protection.

The editorial team of Red Hot Cyber consists of a group of individuals and anonymous sources who actively collaborate to provide early information and news on cybersecurity and computing in general.
-
Business2 weeks ago
The Guardian view on Trump and the Fed: independence is no substitute for accountability | Editorial
-
Tools & Platforms1 month ago
Building Trust in Military AI Starts with Opening the Black Box – War on the Rocks
-
Ethics & Policy2 months ago
SDAIA Supports Saudi Arabia’s Leadership in Shaping Global AI Ethics, Policy, and Research – وكالة الأنباء السعودية
-
Events & Conferences4 months ago
Journey to 1000 models: Scaling Instagram’s recommendation system
-
Jobs & Careers3 months ago
Mumbai-based Perplexity Alternative Has 60k+ Users Without Funding
-
Podcasts & Talks2 months ago
Happy 4th of July! 🎆 Made with Veo 3 in Gemini
-
Education3 months ago
VEX Robotics launches AI-powered classroom robotics system
-
Education2 months ago
Macron says UK and France have duty to tackle illegal migration ‘with humanity, solidarity and firmness’ – UK politics live | Politics
-
Podcasts & Talks2 months ago
OpenAI 🤝 @teamganassi
-
Funding & Business3 months ago
Kayak and Expedia race to build AI travel agents that turn social posts into itineraries