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Regardless of the driver of transformation, your companys culture, leadership, and operating practices must continuously improve to meet the demands of a globally competitive, faster-paced, and technology-enabled world with increasing security and other operational risks.
This is particularly true with enterprise deployments as the capabilities of existing models, coupled with the complexities of many business workflows, led to slower progress than many expected. Assuming a technology can capture these risks will fail like many knowledge management solutions did in the 90s by trying to achieve the impossible.
Gartner’s top predictions for 2025 are as follows: Through 2026, 20% of organizations will use AI to flatten their organizational structure, eliminating more than half of current middle management positions. By 2028, 40% of large enterprises will deploy AI to manipulate and measure employee mood and behaviors, all in the name of profit. “AI
We may look back at 2024 as the year when LLMs became mainstream, every enterprise SaaS added copilot or virtual assistant capabilities, and many organizations got their first taste of agentic AI. AI at Wharton reports enterprises increased their gen AI investments in 2024 by 2.3 CIOs should consider placing these five AI bets in 2025.
Forrester Research this week unleashed a slate of predictions for 2025. 2025 will be about the pursuit of near-term, bottom-line gains while competing for declining consumer loyalty and digital-first business buyers,” Sharyn Leaver, Forrester chief research officer, wrote in a blog post Tuesday.
Vendors are adding gen AI across the board to enterprise software products, and AI developers havent been idle this year either. According to a Bank of America survey of global research analysts and strategists released in September, 2024 was the year of ROI determination, and 2025 will be the year of enterprise AI adoption.
Research firm IDC projects worldwide spending on technology to support AI strategies will reach $337 billion in 2025 — and more than double to $749 billion by 2028. AI spending on the rise Two-thirds (67%) of projected AI spending in 2025 will come from enterprises embedding AI capabilities into core business operations, IDC claims.
TL;DR: Enterprise AI teams are discovering that purely agentic approaches (dynamically chaining LLM calls) dont deliver the reliability needed for production systems. A shift toward structured automation, which separates conversational ability from business logic execution, is needed for enterprise-grade reliability.
Research from Gartner, for example, shows that approximately 30% of generative AI (GenAI) will not make it past the proof-of-concept phase by the end of 2025, due to factors including poor data quality, inadequate risk controls, and escalating costs. [1]
In 2025, thats going to change. Here are five keys to addressing these issues for AI success in 2025. What are the associated risks and costs, including operational, reputational, and competitive? Change management creates alignment across the enterprise through implementation training and support.
The Middle East is rapidly evolving into a global hub for technological innovation, with 2025 set to be a pivotal year in the regions digital landscape. Looking ahead to 2025, Lalchandani identifies several technological trends that will define the Middle Easts digital landscape.
While most provisions of the EU AI Act come into effect at the end of a two-year transition period ending in August 2026, some of them enter force as early as February 2, 2025. particular, companies that use AI systems can share their voluntary commitments to transparency and risk control.
This year saw emerging risks posed by AI , disastrous outages like the CrowdStrike incident , and surmounting software supply chain frailties , as well as the risk of cyberattacks and quantum computing breaking todays most advanced encryption algorithms. To respond, CIOs are doubling down on organizational resilience.
A sharp rise in enterprise investments in generative AI is poised to reshape business operations, with 68% of companies planning to invest between $50 million and $250 million over the next year, according to KPMGs latest AI Quarterly Pulse Survey. However, only 12% have deployed such tools to date.
Enterprises worldwide are harboring massive amounts of data. Interest in turning enterprise data into new revenue is soaring. According to the 2025 State of the CIO survey , 38% of IT leaders say monetizing company data is the most significant business initiative driving their IT investments this year the No.
CIOs perennially deal with technical debts risks, costs, and complexities. While the impacts of legacy systems can be quantified, technical debt is also often embedded in subtler ways across the IT ecosystem, making it hard to account for the full list of issues and risks.
It provides better data storage, data security, flexibility, improved organizational visibility, smoother processes, extra data intelligence, increased collaboration between employees, and changes the workflow of small businesses and large enterprises to help them make better decisions while decreasing costs. Cost management and containment.
The 2024 Enterprise AI Readiness Radar report from Infosys , a digital services and consulting firm, found that only 2% of companies were fully prepared to implement AI at scale and that, despite the hype , AI is three to five years away from becoming a reality for most firms. Is our AI strategy enterprise-wide?
SpyCloud , the leading identity threat protection company, today released its 2025 SpyCloud Annual Identity Exposure Report , highlighting the rise of darknet-exposed identity data as the primary cyber risk facing enterprises today. Additional Report Findings: 17.3
Customer relationship management ( CRM ) software provider Salesforce has updated its agentic AI platform, Agentforce , to make it easier for enterprises to build more efficient agents faster and deploy them across a variety of systems or workflows. Christened Agentforce 2.0, New agent skills in Agentforce 2.0
What will the world of data tools be like at the end of 2025? This will drive a new consolidated set of tools the data team will leverage to help them govern, manage risk, and increase team productivity. What will exist at the end of 2025? The vendor sprawl leaves enterprises to integrate and rationalize their approach.
The key areas we see are having an enterprise AI strategy, a unified governance model and managing the technology costs associated with genAI to present a compelling business case to the executive team. Our research indicates a scramble to identify and experiment with use cases in most business functions within an enterprise.
Copilot Studio allows enterprises to build autonomous agents, as well as other agents that connect CRM systems, HR systems, and other enterprise platforms to Copilot. Then in November, the company revealed its Azure AI Agent Service, a fully-managed service that lets enterprises build, deploy and scale agents quickly.
The company provides industry-specific enterprise software that enhances business performance and operational efficiency. Infor offers applications for enterprise resource planning, supply chain management, customer relationship management and human capital management, among others. The average expected spend for 2024 is 3.7%
Agentic AI was the big breakthrough technology for gen AI last year, and this year, enterprises will deploy these systems at scale. According to a January KPMG survey of 100 senior executives at large enterprises, 12% of companies are already deploying AI agents, 37% are in pilot stages, and 51% are exploring their use.
See also: Gen AI in 2025: Playtime is over, time to get practical. The challenge of ROI in innovation The same IDC survey reveals that 58% of IT executives anticipate higher IT spending in 2025 compared with 2024. million in 2025 to $7.45 million in 2025 to $7.45
Agentic AI is the new frontier in AI evolution, taking center stage in todays enterprise discussion. UIPaths 2025 Agentic AI Report surveyed US IT execs from companies with $1 billion or more in revenue and found that 93% are highly interested in agentic AI for their business. We use AI to scale our mission, not replace our people.
As concerns about AI security, risk, and compliance continue to escalate, practical solutions remain elusive. as AI adoption and risk increases, its time to understand why sweating the small and not-so-small stuff matters and where we go from here. Additionally, does your enterprise flat-out restrict or permit public LLM access?
Agentic AI, the more focused alternative to general-purpose generative AI, is gaining momentum in the enterprise, with Forrester having named it a top emerging technology for 2025 in June. The reason is because enterprises look for some predictability. Potentially good for customers, but maybe not for shareholder returns.
Business risk (liabilities): “Our legacy systems increase our cybersecurity exposure by 40%.” Our research shows 52% of organizations are increasing AI investments through 2025 even though, along with enterprise applications, AI is the primary contributor to tech debt.
14, 2025, many CIOs find themselves at a crossroads, with some considering Copilot+ certified AI PCs as part of their enterprise fleet plans for Windows 11. OEMs that have shipped or are readying AI PCs for 2025 or 2026 include Dell, Acer, Asus, HP, Lenovo, Samsung, and Microsoft.
And, yes, enterprises are already deploying them. Adding smarter AI also adds risk, of course. “At The big risk is you take the humans out of the loop when you let these into the wild.” When it comes to security, though, agentic AI is a double-edged sword with too many risks to count, he says. “We
April 30, 2025 insightsoftware , the most comprehensive provider of solutions for the Office of the CFO, introduces EZLease Lessor , a lease lifecycle management solution that reduces risk, cost, and complexity for lessors. This allows teams to focus on higher-value, strategic tasks.
Our latest 2025 BARC Score on Data Intelligence Platforms reveals four key trends that are reshaping how organizations harness their data assets. You need tools that provide comprehensive oversight of your AI systems, from cataloging the unstructured data feeding your models to assessing the risks associated with AI-driven decisions.
Meanwhile, Gartner predicts at least 30% of gen AI projects will be abandoned after the proof-of-concept stage by 2025. That high level of democratization doesn’t come without risks, and that’s where CIOs, as the guardians of enterprise technology, play a crucial role.
In the European Union, for example, three-quarters of organizations are in the early stages of doing so (IDC’s Future Enterprise Resiliency and Spending Survey, Wave 3, April 2023). Back to the good news: Organizations are slowly conquering this issue. Businesses have no choice but to adapt to these new regulations.
There’s already more low-quality AI content flooding search results, and this can hurt employees looking for information both on the public web and in enterprise knowledge repositories. And we’re at risk of being burned out.” Finding a result that’s actually useful can be like looking for a needle in a haystack.
These IT pros are tasked with overseeing the adoption of cloud-based AI solutions in an enterprise environment, further expanding the responsibility scope of the role. These IT pros can help navigate the process, which can take years navigating potential risks and ensuring a smooth transition.
Predicts 2021: Data and Analytics Leaders Are Poised for Success but Risk an Uncertain Future : By 2023, 50% of chief digital officers in enterprises without a chief data officer (CDO) will need to become the de facto CDO to succeed.
Companies are leaning into delivering on data intelligence and governance initiatives in 2025 according to our recent State of Data Intelligence research. With a variety of providers and offerings addressing data intelligence and governance needs, it can be easy to feel overwhelmed in selecting the right solution for your enterprise.
They will oversee four working groups, each focusing on different aspects of AI governance — transparency and copyright, risk identification and assessment, technical risk mitigation, and internal risk management for general-purpose AI providers.
Between building gen AI features into almost every enterprise tool it offers, adding the most popular gen AI developer tool to GitHub — GitHub Copilot is already bigger than GitHub when Microsoft bought it — and running the cloud powering OpenAI, Microsoft has taken a commanding lead in enterprise gen AI.
In IDCs April 2024 CIO Poll Survey of 105 senior IT professionals and CIOs, developing better IT governance and enterprise architecture emerged as one of the top priorities for 2024, ranking fourth. It is fundamental for AI and essential for reducing cybersecurity risks or streamlining cloud migration processes, among other things.
To fulfill todays data-driven agendas, many enterprises need an evolved perspective on data governance. Good data governance provides guardrails that enable enterprises to act fast while protecting the business from risks related to regulatory requirements, data-quality issues and data-reliability concerns.
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