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Gartner: 30% of GenAI Projects Will Be Abandoned After Proof of Concept by End of 2025

At least 30% of generative AI (GenAI) projects will be abandoned after proof of concept by the end of 2025, due to poor data quality, inadequate risk controls, escalating costs or unclear business value, according to Gartner, Inc.

"After last year's hype, executives are impatient to see returns on GenAI investments, yet organizations are struggling to prove and realize value,” said Rita Sallam, Distinguished VP Analyst at Gartner. "As the scope of initiatives widen, the financial burden of developing and deploying GenAI models is increasingly felt."

A major challenge for organizations arises in justifying the substantial investment in GenAI for productivity enhancement, which can be difficult to directly translate into financial benefit, according to Gartner. Many organizations are leveraging GenAI to transform their business models and create new business opportunities. However, these deployment approaches come with significant costs, ranging from $5 million to $20 million.

"Unfortunately, there is no one size fits all with GenAI, and costs aren't as predictable as other technologies," said Sallam. "What you spend, the use cases you invest in and the deployment approaches you take, all determine the costs. Whether you're a market disruptor and want to infuse AI everywhere, or you have a more conservative focus on productivity gains or extending existing processes, each has different levels of cost, risk, variability and strategic impact."

Regardless of AI ambition, Gartner research indicates GenAI requires a higher tolerance for indirect, future financial investment criteria versus immediate return on investment (ROI). Historically, many CFOs have not been comfortable with investing today for indirect value in the future. This reluctance can skew investment allocation to tactical versus strategic outcomes.

Realizing Business Value

Earlier adopters across industries and business processes are reporting a range of business improvements that vary by use case, job type and skill level of the worker. According to a recent Gartner survey, respondents reported 15.8% revenue increase, 15.2% cost savings and 22.6% productivity improvement on average. The survey of 822 business leaders was conducted between September and November 2023.

"This data serves as a valuable reference point for assessing the business value derived from GenAI business model innovation," said Sallam. "But it's important to acknowledge the challenges in estimating that value, as benefits are very company, use case, role and workforce specific. Often, the impact may not be immediately evident and may materialize over time. However, this delay doesn't diminish the potential benefits."

Calculating Business Impact

By analyzing the business value and the total costs of GenAI business model innovation, organizations can establish the direct ROI and future value impact, according to Gartner. This serves as a crucial tool for making informed investment decisions about GenAI business model innovation.

"If the business outcomes meet or exceed expectations, it presents an opportunity to expand investments by scaling GenAI innovation and usage across a broader user base, or implementing it in additional business divisions," said Sallam. "However, if they fall short, it may be necessary to explore alternative innovation scenarios. These insights help organizations strategically allocate resources and determine the most effective path forward."

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Gartner: 30% of GenAI Projects Will Be Abandoned After Proof of Concept by End of 2025

At least 30% of generative AI (GenAI) projects will be abandoned after proof of concept by the end of 2025, due to poor data quality, inadequate risk controls, escalating costs or unclear business value, according to Gartner, Inc.

"After last year's hype, executives are impatient to see returns on GenAI investments, yet organizations are struggling to prove and realize value,” said Rita Sallam, Distinguished VP Analyst at Gartner. "As the scope of initiatives widen, the financial burden of developing and deploying GenAI models is increasingly felt."

A major challenge for organizations arises in justifying the substantial investment in GenAI for productivity enhancement, which can be difficult to directly translate into financial benefit, according to Gartner. Many organizations are leveraging GenAI to transform their business models and create new business opportunities. However, these deployment approaches come with significant costs, ranging from $5 million to $20 million.

"Unfortunately, there is no one size fits all with GenAI, and costs aren't as predictable as other technologies," said Sallam. "What you spend, the use cases you invest in and the deployment approaches you take, all determine the costs. Whether you're a market disruptor and want to infuse AI everywhere, or you have a more conservative focus on productivity gains or extending existing processes, each has different levels of cost, risk, variability and strategic impact."

Regardless of AI ambition, Gartner research indicates GenAI requires a higher tolerance for indirect, future financial investment criteria versus immediate return on investment (ROI). Historically, many CFOs have not been comfortable with investing today for indirect value in the future. This reluctance can skew investment allocation to tactical versus strategic outcomes.

Realizing Business Value

Earlier adopters across industries and business processes are reporting a range of business improvements that vary by use case, job type and skill level of the worker. According to a recent Gartner survey, respondents reported 15.8% revenue increase, 15.2% cost savings and 22.6% productivity improvement on average. The survey of 822 business leaders was conducted between September and November 2023.

"This data serves as a valuable reference point for assessing the business value derived from GenAI business model innovation," said Sallam. "But it's important to acknowledge the challenges in estimating that value, as benefits are very company, use case, role and workforce specific. Often, the impact may not be immediately evident and may materialize over time. However, this delay doesn't diminish the potential benefits."

Calculating Business Impact

By analyzing the business value and the total costs of GenAI business model innovation, organizations can establish the direct ROI and future value impact, according to Gartner. This serves as a crucial tool for making informed investment decisions about GenAI business model innovation.

"If the business outcomes meet or exceed expectations, it presents an opportunity to expand investments by scaling GenAI innovation and usage across a broader user base, or implementing it in additional business divisions," said Sallam. "However, if they fall short, it may be necessary to explore alternative innovation scenarios. These insights help organizations strategically allocate resources and determine the most effective path forward."

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One of the earliest lessons I learned from architecting throughput-heavy services is that simplicity wins repeatedly: fewer moving parts, loosely coupled execution (fewer synchronous calls), and precise timing metering. You want data and decisions to travel the shortest possible path. The goal is to build a system where every strategy and each line of code (contention is the key metric) complements the decision trees ...

As discussions around AI "autonomous coworkers" accelerate, many industry projections assume that agents will soon operate alongside human staff in making decisions, taking actions, and managing tasks with minimal oversight. But a growing number of critics (including some of the developers building these systems) argue that the industry still has a long way to go to be able to treat AI agents like fully trusted teammates ...

Enterprise AI has entered a transformational phase where, according to Digitate's recently released survey, Agentic AI and the Future of Enterprise IT, companies are moving beyond traditional automation toward Agentic AI systems designed to reason, adapt, and collaborate alongside human teams ...

The numbers back this urgency up. A recent Zapier survey shows that 92% of enterprises now treat AI as a top priority. Leaders want it, and teams are clamoring for it. But if you look closer at the operations of these companies, you see a different picture. The rollout is slow. The results are often delayed. There's a disconnect between what leaders want and what their technical infrastructure can handle ...

Kyndryl's 2025 Readiness Report revealed that 61% of global business and technology leaders report increasing pressure from boards and regulators to prove AI's ROI. As the technology evolves and expectations continue to rise, leaders are compelled to generate and prove impact before scaling further. This will lead to a decisive turning point in 2026 ...

Cloudflare's disruption illustrates how quickly a single provider's issue cascades into widespread exposure. Many organizations don't fully realize how tightly their systems are coupled to thirdparty services, or how quickly availability and security concerns align when those services falter ... You can't avoid these dependencies, but you can understand them ...

If you work with AI, you know this story. A model performs during testing, looks great in early reviews, works perfectly in production and then slowly loses relevance after operating for a while. Everything on the surface looks perfect — pipelines are running, predictions or recommendations are error-free, data quality checks show green; yet outcomes don't meet the ground reality. This pattern often repeats across enterprise AI programs. Take for example, a mid-sized retail banking and wealth-management firm with heavy investments in AI-powered risk analytics, fraud detection and personalized credit-decisioning systems. The model worked well for a while, but transactions increased, so did false positives by 18% ...

Basic uptime is no longer the gold standard. By 2026, network monitoring must do more than report status, it must explain performance in a hybrid-first world. Networks are no longer just static support systems; they are agile, distributed architectures that sit at the very heart of the customer experience and the business outcomes ... The following five trends represent the new standard for network health, providing a blueprint for teams to move from reactive troubleshooting to a proactive, integrated future ...

APMdigest's Predictions Series concludes with 2026 AI Predictions — industry experts offer predictions on how AI and related technologies will evolve and impact business in 2026. Part 5, the final installment, covers AI's impacts on IT teams ...