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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.
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.
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.
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.
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?
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.
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.
In early 2025, security researchers uncovered the Murdoc Botnet, a new strain of the infamous Mirai malware. Data privacy risks. Weak encryption or insecure APIs create data leakage risks. Insecure third-party firmware, libraries and components can introduce risks far upstream of deployment. Weak authentication.
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.
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.
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.
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.
In 2025, the challenge will be turning those agendas into reality. Learn from their experience to help put AI to work in your enterprise. 5:34 : You work with the folks at Azure, so presumably you know what actual enterprises are doing with generative AI. Can you give us an idea of what enterprises are starting to deploy?
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.
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