Generative Artificial Intelligence (GenAI) is a transformative technology reshaping various industries. However, a recent Gartner report highlights that around 30% of GenAI projects may not progress beyond the proof-of-concept stage by 2025 due to challenges such as high costs, unclear business value, and implementation complexities.
Table of Contents
Introduction to GenAI Challenges
According to a recent report by Gartner, approximately 30% of current projects in Generative Artificial Intelligence (GenAI) are expected to be discontinued by the end of 2025. This projected drop-off is attributed to several factors, including poor data quality, insufficient risk management, escalating costs, and unclear business value. These hurdles are making it challenging for organizations to move beyond the proof of concept stage. For instance, a tech startup attempting to leverage GenAI for content generation faced difficulties when the data sets used were inconsistent, resulting in subpar output and eventually leading to project abandonment.
The Impatience of Executives for Returns
Following the immense hype surrounding GenAI last year, executives are eager to see returns on their investments. However, many organizations are finding it challenging to demonstrate tangible value. As the scope of these initiatives expands, the financial burden of developing and deploying GenAI models becomes increasingly apparent. A real-world example includes a retail company investing heavily in GenAI for personalized customer experiences, only to find that the cost of integrating the technology outweighed the immediate benefits.
Justifying Investment in GenAI for Productivity Gains
One significant challenge noted in the report is the difficulty organizations face in justifying the substantial investments required for GenAI projects aimed at enhancing productivity. Unlike straightforward cost-saving measures, productivity gains can be hard to quantify in financial terms. For example, a logistics firm may use GenAI to optimize its supply chain. While efficiency may improve, translating these improvements into direct financial gains can be complex.
The High Costs of GenAI Deployment
The report highlights that many organizations are leveraging GenAI to transform business models and create new opportunities. However, the costs associated with these deployments can range significantly, from $5 million to $20 million. An example includes a financial services company that developed a GenAI model to automate customer service. Despite the potential for long-term savings, the initial costs were so high that the company reconsidered the project’s viability.
The Lack of Predictability in GenAI Costs
Rita Sallam, distinguished VP analyst at Gartner, pointed out that GenAI does not have a one-size-fits-all cost structure. The expenses depend on various factors, including the use cases, deployment methods, and organizational objectives. For instance, a healthcare provider aiming to use GenAI for patient diagnostics may encounter unpredictable costs due to the need for specialized data and compliance requirements.
Strategic vs. Tactical Investment in GenAI
The report emphasizes that regardless of an organization’s AI ambition, GenAI requires a higher tolerance for future financial investment with indirect returns. Historically, chief financial officers (CFOs) have been reluctant to allocate funds to projects with uncertain, long-term benefits. A case in point is a manufacturing company that hesitated to invest in GenAI for predictive maintenance, preferring instead to focus on immediate cost-saving measures.
Early Adopters of GenAI Report Mixed Results
Early adopters of GenAI across various industries and business processes have reported a range of business improvements. These improvements vary depending on the specific use case, job type, and worker skill level. For example, a marketing firm using GenAI for customer segmentation reported a 15.8% increase in revenue, highlighting the potential for significant business benefits. However, these benefits are not uniform across all implementations.
Measuring the Business Value of GenAI
Gartner’s recent survey found that organizations leveraging GenAI reported, on average, a 15.2% reduction in costs and a 22.6% improvement in productivity. While these figures provide a benchmark for assessing the potential business value, it’s crucial to note that the benefits are highly specific to the company, use case, role, and workforce. For instance, an automotive company using GenAI for quality control experienced improved efficiency but struggled to quantify the exact financial benefits.
The Challenge of Estimating GenAI Value
Estimating the value derived from GenAI business model innovation is challenging due to the variability in benefits across different organizations and use cases. Often, the impact of GenAI implementations may not be immediately evident and may take time to materialize. For example, a tech company implementing GenAI for software testing found that the long-term benefits, such as reduced time to market, became apparent only after several months.
Conclusion: The Future of GenAI Investments
Despite the challenges and the potential for many projects to be discontinued, the future of GenAI remains promising. As organizations gain more experience and refine their approaches, the ability to derive substantial business value from GenAI is likely to improve. Companies are encouraged to carefully assess their investment strategies, considering both the potential risks and the long-term benefits. For instance, a retail giant investing in GenAI for inventory management has laid the groundwork for future enhancements, positioning itself to capitalize on the technology’s evolving capabilities.
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Information in Table format
| Section | Content | Real-Life Example |
|---|---|---|
| Introduction to GenAI Challenges | Around 30% of GenAI projects may not progress beyond proof of concept due to poor data quality, inadequate risk management, high costs, and unclear business value. | A tech startup using inconsistent data sets for content generation had to abandon the project due to poor results. |
| The Impatience of Executives for Returns | Executives are eager for returns on GenAI investments, but many struggle to prove value, especially as project costs increase. | A retail company invested in GenAI for personalized customer experiences but found the costs outweighing benefits. |
| Justifying Investment in GenAI for Productivity Gains | Organizations find it hard to justify significant investments in GenAI aimed at enhancing productivity due to the difficulty in quantifying financial benefits. | A logistics firm used GenAI to optimize supply chain operations, but struggled to directly link improvements to profits. |
| The High Costs of GenAI Deployment | Deploying GenAI models can cost between $5 million to $20 million, presenting a significant financial challenge for businesses. | A financial services company reconsidered its GenAI customer service project due to high initial costs. |
| The Lack of Predictability in GenAI Costs | Costs associated with GenAI vary based on use cases, deployment methods, and organizational objectives. | A healthcare provider faced unpredictable costs due to specialized data needs and compliance requirements for diagnostics. |
| Strategic vs. Tactical Investment in GenAI | GenAI requires a higher tolerance for future financial investments with indirect returns, making CFOs hesitant to invest in uncertain long-term benefits. | A manufacturing company hesitated to invest in GenAI for predictive maintenance, focusing on immediate savings instead. |
| Early Adopters of GenAI Report Mixed Results | Business improvements from GenAI vary widely by industry, use case, and skill level, with some reporting revenue increases, cost savings, and productivity gains. | A marketing firm saw a 15.8% revenue increase using GenAI for customer segmentation. |
| Measuring the Business Value of GenAI | Companies reported an average 15.2% cost reduction and 22.6% productivity improvement from GenAI, but benefits vary significantly and can be hard to quantify. | An automotive company using GenAI for quality control improved efficiency but struggled to quantify financial benefits. |
| The Challenge of Estimating GenAI Value | Estimating the value of GenAI is difficult due to the specific nature of each implementation, with benefits often not immediately evident. | A tech company saw long-term benefits, like reduced time to market, from using GenAI for software testing. |
| Conclusion: The Future of GenAI Investments | Despite challenges, GenAI has promising potential. Organizations should carefully assess investment strategies, considering both risks and long-term benefits. | A retail giant investing in GenAI for inventory management is positioning itself for future enhancements and gains. |
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FAQs
1. What percentage of GenAI projects are expected to be discontinued by 2025?
According to a Gartner report, approximately 30% of Generative Artificial Intelligence (GenAI) projects are expected to be discontinued by the end of 2025. This is largely due to challenges such as poor data quality, inadequate risk controls, escalating costs, and unclear business value.
2. Why are some GenAI projects being dropped?
Some GenAI projects are being dropped because organizations struggle with issues like poor data quality, inadequate risk controls, and escalating costs. Additionally, there can be challenges in demonstrating clear business value, which makes it difficult to justify continued investment.
3. What are the key challenges in proving the value of GenAI investments?
The key challenges in proving the value of GenAI investments include justifying the substantial initial costs, translating productivity enhancements into direct financial benefits, and dealing with the unpredictable nature of expenses. Organizations often find it difficult to measure the immediate return on investment (ROI) from these projects.
4. How much can it cost to deploy GenAI models?
Deploying GenAI models can be quite costly, with expenses ranging from $5 million to $20 million, depending on the scope and complexity of the project. These costs can vary significantly based on factors such as the specific use cases, deployment approaches, and the scale of implementation.
5. Is there a predictable cost structure for GenAI projects?
No, there isn’t a predictable cost structure for GenAI projects. The costs are influenced by various factors, including the specific use cases being targeted, the deployment methods chosen, and the organizational objectives. Each project has unique cost considerations, making budgeting challenging.
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6. How do early adopters of GenAI report their business improvements?
Early adopters of GenAI report a range of business improvements, which vary depending on the specific use cases and the context of the implementation. According to Gartner’s survey, companies have reported an average 15.8% increase in revenue, a 15.2% reduction in costs, and a 22.6% improvement in productivity.
7. What difficulties do organizations face in measuring the business value of GenAI?
Organizations face difficulties in measuring the business value of GenAI because the benefits can be highly specific to the company, use case, and workforce. Additionally, the impact of GenAI projects may not be immediately visible, as some benefits materialize over time, making it challenging to quantify them upfront.
8. Why might CFOs be reluctant to invest in GenAI projects?
Chief financial officers (CFOs) may be reluctant to invest in GenAI projects because these initiatives often require a higher tolerance for indirect and future financial returns. Many CFOs prefer projects with clear, immediate ROI, which can lead to a preference for tactical investments over strategic, long-term projects like GenAI.
9. Can the benefits of GenAI vary across different industries?
Yes, the benefits of GenAI can vary significantly across different industries and even within the same industry based on the specific use case. For instance, a tech company might see improvements in software testing efficiency, while a retail company could benefit from enhanced customer personalization. The value and impact are often unique to the organization’s context and goals.
10. What is the outlook for the future of GenAI investments?
The future of GenAI investments remains promising despite the challenges. As organizations continue to refine their approaches and gain more experience, they are likely to improve their ability to derive substantial business value from GenAI. Companies are advised to carefully assess their investment strategies, considering both the potential risks and the long-term benefits of these technologies.