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Despite AI’s potential to transform businesses, many senior technology leaders find themselves wrestling with unpredictable expenses, uneven productivity gains, and growing risks as AI adoption scales, Gartner said. This creates new risks around data privacy, security, and consistency, making it harder for CIOs to maintain control.
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.
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. Upskilling and seamless integration into workflows will drive adoption and ROI.
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.
But as enterprises increasingly experience pilot fatigue and pivot toward seeking practical results from their efforts , learnings from these experiments wont be enough the process itself may need to produce more targeted success rates. A lot of efforts are not gen AI, but they are trying to inject some gen AI things into it, he explains.
By Bryan Kirschner, Vice President, Strategy at DataStax From the Wall Street Journal to the World Economic Forum , it seems like everyone is talking about the urgency of demonstrating ROI from generative AI (genAI). GenAI itself can report week-on-week progress, putting it to work across your organization–including the ROI.
The rise of the cloud continues Global enterprise spend on cloud infrastructure and storage products for cloud deployments grew nearly 40% year-over-year in Q1 of 2024 to $33 billion, according to IDC estimates. BPS also adopts proactive thinking, a risk-based framework for strategic alignment and compliance with business objectives.
While the ROI of any given AI project remains uncertain , one thing is becoming clear: CIOs will be spending a whole lot more on the technology in the years ahead. 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.
Jayesh Chaurasia, analyst, and Sudha Maheshwari, VP and research director, wrote in a blog post that businesses were drawn to AI implementations via the allure of quick wins and immediate ROI, but that led many to overlook the need for a comprehensive, long-term business strategy and effective data management practices.
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.
For many years, AI was an experimental risk for companies. Today, AI is not a brand new concept and most enterprises have at least explored AI implementation. As of 2020, 68% of enterprises had used AI, having already adopted AI applications or introduced AI on some level into their business processes.
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. Focus on delivering immediate change in a self-funding way.
According to a separate study on the AI readiness of Indian enterprises conducted by EY and Indian IT industry body Nasscom, enterprises are also holding back the deployment of AI due to concerns about data security, privacy, brand reputation, and the safety and security of people and equipment.
Most enterprises want to avoid expending unnecessary time, effort, and resources on licensing issues, so they can focus on maximizing value and results. Unfortunately, Oracle’s enterprise license agreements, and, more specifically, ULAs, typically require consistent oversight and proper management to ensure successful outcomes.
But alongside its promise of significant rewards also comes significant costs and often unclear ROI. Ineffective cost management: Over 22% of IT executives highlight challenges in managing costs and developing clear ROI methodologies. Lets begin by examining the specific cost-related concerns CIOs face when adopting GenAI technologies.
One of the most important parameters for measuring the success of any technology implementation is the return on investment (ROI). Providing a compelling ROI on technology initiatives also puts CIOs in a stronger position for securing support and funds from the business for future projects. Deploy scalable technology.
Its the year organizations will move their AI initiatives into production and aim to achieve a return on investment (ROI). What are the associated risks and costs, including operational, reputational, and competitive? Change management creates alignment across the enterprise through implementation training and support.
Generative AI has seen faster and more widespread adoption than any other technology today, with many companies already seeing ROI and scaling up use cases into wide adoption. Vendors are adding gen AI across the board to enterprise software products, and AI developers havent been idle this year either.
For enterprise architecture, success is often contingent on having clearly defined business goals. This is especially true in modern enterprise architecture, where value-adding initiatives are favoured over strictly “foundational,” “keeping the lights on,” type duties.
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. This can be great for technically-savvy customers but has the risk of not being sufficiently abstracted from AI costs to hold value over time, he says.
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.
Microsoft is opening another route for extending the reach of its Copilot offerings in the enterprise through an expanded partnership with global professional services company Cognizant. The announcement comes amid reluctance among some CIOs regarding the ROI of generative AI copilots.
Enterprise resource planning (ERP) is ripe for a major makeover thanks to generative AI, as some experts see the tandem as a perfect pairing that could lead to higher profits at enterprises that combine them. At the same time, gen AI will make bill collections faster and cheaper, leading to increased profits, the report adds.
While many organizations have implemented AI, the need to keep a competitive edge and foster business growth demands new approaches: simultaneously evolving AI strategies, showcasing their value, enhancing risk postures and adopting new engineering capabilities. This requires a holistic enterprise transformation. times higher ROI.
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). Overcoming this hurdle requires strong leadership and good data that will lead to effectively investing budgets in ways that yield a measurable ROI.
And as gen AI is deployed by more companies, especially for high-risk, public-facing use cases, we’re likely to see more examples like this. But only 33% of respondents said they’re working to mitigate cybersecurity risks, down from 38% last year. But plans are progressing slower than anticipated because of associated risks,” she says.
This is why many enterprises are seeing a lot of energy and excitement around use cases, yet are still struggling to realize ROI. So, to maximize the ROI of gen AI efforts and investments, it’s important to move from ad-hoc experimentation to a more purposeful strategy and systematic approach to implementation.
Data is what economists would call a non-rival risk, non-depleting progenitor of assets,” Laney says. times more likely when they demonstrated ROI on their BI or data analytics investments. Product-based thinking means that there’s an owner in the business, managing it strategically with an ROI attitude.
BAS is one of the top features in security posture management platforms for enterprises. It is not only able to check whether or not security controls are working the way they should; it also maximizes the ROI on these controls.
The company received the Asia Responsible Enterprise Awards 2022 for circular economy leadership , which recognized IVL’s successful PET Bottles Recycling to Personal Protection Equipment (PPE) Distribution project. About four years ago, IVL expanded the use of risk acceptance at its PNO facility in Texas to establish next-inspection plans.
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.
According to AI at Wartons report on navigating gen AIs early years, 72% of enterprises predict gen AI budget growth over the next 12 months but slower increases over the next two to five years. Proving the ROI of AI can be elusive , but rushing to achieve it can prove costly.
Because it’s so different from traditional software development, where the risks are more or less well-known and predictable, AI rewards people and companies that are willing to take intelligent risks, and that have (or can develop) an experimental culture. What delivers the greatest ROI? How do you select what to work on?
“Such discussions ensure the integration of cybersecurity initiatives and resource requirements in the enterprise’s business goals and objectives,” he adds. The discussions address changing regulatory and compliance requirements, and reveal vulnerabilities and threats for risk mitigation.”
Lack of clear, unified, and scaled data engineering expertise to enable the power of AI at enterprise scale. Regulations and compliance requirements, especially around pricing, risk selection, etc., What do you recommend to organizations to harness this but also show a solid ROI? It is fast and slow.
In collaboration with our peers, we have a solid business sense that carefully weighs innovation and risk in order to gain valuable ROI while protecting the organization from all forms of risk associated with each project. If reversible, then there’s clearly less risk. What’s new and different today?
In a research note, Gartner said DeepSeek challenges the prevailing gen AI cost structures and methodologies, underscoring the inefficiencies in current leading vendor pricing models that can lead to negative ROI for high-value use cases deployed at scale.
However, embedding ESG into an enterprise data strategy doesnt have to start as a C-suite directive. If sustainability-related data projects fail to demonstrate a clear financial impact, they risk being deprioritized in favor of more immediate business concerns.
More generally, low-quality data can impact productivity, bottom line, and overall ROI. No, its ultimate goal is to increase return on investment (ROI) for those business segments that depend upon data. Industry-wide, the positive ROI on quality data is well understood. Data Quality Management Best Practices.
Many of those gen AI projects will fail because of poor data quality, inadequate risk controls, unclear business value , or escalating costs , Gartner predicts. In the enterprise, huge expectations have been partly driven by the major consumer reaction following the release of ChatGPT in late 2022, Stephenson suggests.
Attacks against OT systems pose risks beyond financial losses. Colonial Pipeline, and the Ukraine power grid , to name a few, all led to potential health risks and operational shutdown of critical facilities. The first is the ability to get to ROI faster. We hear about these types of attacks with distressing regularity.
Forrester recently released its “Now Tech: Enterprise Architecture Management Suites for Q1 2020” to give organizations an enterprise architecture (EA) playbook. It also highlights select enterprise architecture management suite (EAMS) vendors based on size and functionality, including erwin. Guess what?
For the evolution of its enterprise storage infrastructure, Petco had stringent requirements to significantly improve speed, performance, reliability, and cost efficiency. This bank needed to upgrade its enterprise storage infrastructure as part of a major upgrade of online banking applications with a third-party provider.
And Doug Shannon, automation and AI practitioner, and Gartner peer community ambassador, says the vast majority of enterprises are now focused on two categories of use cases that are most likely to deliver positive ROI. Classifiers are provided in the toolkits to allow enterprises to set thresholds. “We
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