What is a Realistic ROI on Gen AI?

ROI on Gen AI

Investing in generative artificial intelligence (Gen AI) holds the promise of transforming business operations. However, to reap the benefits, it is crucial to set realistic expectations regarding the returns on investment (ROI). This article explores what ROI on Gen AI can reasonably be expected, focusing on its application in various industries, including healthcare, financial services, mining, and energy and utilities.

Business Objectives Addressed by Gen AI

Generative AI can address several critical business objectives, making it a valuable investment. Primarily, it enhances efficiency by automating repetitive tasks and processes, allowing employees to focus on more strategic activities. Additionally, it significantly reduces costs by minimizing operational and production expenses. In terms of customer experience, Gen AI offers the ability to personalize interactions and services, leading to higher satisfaction and loyalty. Furthermore, it drives innovation by enabling the creation of new products and services thereby supporting better decision-making by providing deep insights through data analysis.

Despite all the potential benefits, there are pitfalls to learning and implementing a brand-new technology. Industry research leader Gartner forecasts the current Generative AI surge of investment will ultimately hit resistance. A focus on Return on Investment will have an impact.

By 2025, growth in 90% of enterprise deployments of GenAI will slow as costs exceed value.

Gartner (source)

Business Use Cases of ROI on Gen AI

Consider the healthcare industry, where Gen AI can analyze vast amounts of patient data to predict illnesses before they become severe. By automating administrative tasks, such as scheduling and record-keeping, healthcare professionals can dedicate more time to patient care, thus improving overall efficiency and reducing costs.

In financial services, Gen AI plays a crucial role in automated fraud detection and risk assessment. These systems can analyze transactions in real-time, identifying unusual patterns that may indicate fraudulent activities. Moreover, Gen AI can provide personalized financial advice to customers, enhancing their experience and satisfaction.

In the mining sector, Gen AI optimizes resource extraction processes, ensuring that operations are conducted in the most efficient manner possible. By predicting equipment failures, it helps in scheduling preventive maintenance, thereby reducing downtime and associated costs.

The energy and utilities sector also benefits significantly from Gen AI. It can optimize energy usage patterns, reducing waste and improving efficiency. Predictive maintenance powered by Gen AI ensures that equipment runs smoothly, preventing costly breakdowns and service interruptions.

How Gen AI Initiatives Deliver ROI

The benefits of Gen AI initiatives translate into tangible ROI on Gen AI in several ways. First, by improving efficiency and productivity, businesses can save valuable time and allocate resources more effectively. This leads to higher productivity and reduces operational costs. For instance, a company that automates its customer service with AI chatbots can handle more inquiries without increasing staff numbers, thereby saving costs.

Cost savings are another significant benefit. By reducing the need for manual labor and minimizing errors, Gen AI helps businesses save money. In manufacturing, for example, AI can optimize production lines, reducing waste and lowering production costs. Enhanced customer experience is yet another advantage. Personalized interactions driven by Gen AI improve customer satisfaction and loyalty, which can lead to increased sales and repeat business.

Innovation and growth are crucial aspects of Gen AI investment. Companies that adopt AI can innovate faster, creating new products and services that open up new revenue streams and boost market competitiveness. Furthermore, better decision-making is facilitated by Gen AI’s ability to analyze vast amounts of data quickly, providing actionable insights that drive growth and efficiency.

Levels of Investment Return

Another challenge of investing in new technology is how and what to measure as a basis for your future return on investment. KPMG offers these insights based on recent survey insights (source):

  • 51% of leaders are currently measuring GenAI-related ROI through productivity gains, followed by employee satisfaction (48%) and revenue generated (47%)
  • 54% of leaders expect new business models to support their growth strategies in the next 12 months, followed by new product and revenue streams (46%), productivity (39%) and profitability (31%)

The true ROI for a Gen AI investment is the incremental returns achieved over and above the current programs already in place. Herein lies the challenge – a productivity gain can be hard to allocate to multiple overlapping initiatives.

Evaluate ROI on Gen AI By Strategic Imperative

Gartner suggests grouping your Gen AI initiatives into three strategic “buckets” of either a “quick win”, a “differentiating use case,” or a “transformative initiative.” This approach lets you compare the investment of Gen AI to other investments based on the level of strategic imperative to help provide guidance. With this logic, the returns from Gen AI investments can be categorized into three levels: break-even, moderate return, and high return.

In a break-even scenario, the returns match the investment costs. This is common during the initial stages of implementing Gen AI when setup costs are high. However, the business gains valuable experience and data to refine its AI strategies. For example, a hospital investing in an AI system to manage patient data might initially see cost savings from reduced administrative tasks that just cover the investment. This could be classified as a “quick win.”

A moderate return involves higher gains than the initial investment but is still modest. This level often occurs when Gen AI systems become more integrated and optimized within business processes. In the financial services sector, an AI-driven fraud detection system might significantly reduce fraud losses, providing a moderate return on investment. This type of project might also point to different ways to assess fraud that might lead to a more positive customer experience. While intangible, there is the potential for industry differentiation.

High ROI on Gen AI can lead to substantial cost savings, efficiency improvements, or revenue growth. These returns are typically seen when AI is fully integrated and optimized within the business. In mining, for instance, a Gen AI system that predicts equipment failures with high accuracy can drastically reduce downtime, leading to significant cost savings and increased productivity. These returns will likely take longer to implement and recognize, so could be viewed as more of a strategic business investment, so measured differently.

Industry-Specific Examples of ROI

In healthcare, implementing AI for administrative tasks can initially save time equivalent to investment costs, achieving a break-even return. As AI diagnostics become more sophisticated, they can reduce unnecessary tests and procedures, leading to moderate returns. Over the long term, AI-driven personalized treatment plans can improve patient outcomes and reduce hospital readmissions, resulting in high returns.

In financial services, the initial implementation of AI chatbots can reduce customer service costs to match the investment, achieving a break-even return. As AI-driven investment strategies yield higher returns for clients, the firm’s profits can see a moderate return. Comprehensive AI systems for fraud detection can save millions, far exceeding the investment cost, thus providing high returns.

In the mining industry, AI for equipment monitoring can prevent major failures, achieving a break-even return. As AI optimizes mining operations, resource extraction efficiency improves, providing solid returns. Predictive maintenance powered by AI can drastically reduce downtime, leading to significant productivity boosts and high returns.

The energy and utilities sector can see break-even returns by implementing AI systems for energy usage optimization, initially saving on energy costs equal to the investment. Predictive maintenance can then reduce repair costs and extend equipment lifespan, resulting in moderate returns. AI optimizing energy distribution can lead to significant savings and efficiency improvements, achieving high returns.

Reasonable Timeframes for Return on Investment

The timeframe for seeing returns on Gen AI investments varies depending on the industry, the scale of the project, and the integration level of the AI system. Short-term returns, within 6-12 months, often align with break-even outcomes. Medium-term returns, within 1-3 years, typically reflect moderate gains as AI systems become more integrated and optimized. Long-term returns, spanning 3-5 years, usually yield high returns as businesses fully integrate and optimize their AI systems, leading to substantial cost savings, efficiency improvements, and new revenue streams.

Setting Realistic Expectations

Investing in Gen AI requires realistic expectations regarding ROI. Initial costs can be high, and returns might take time to materialize. However, the long-term benefits can be substantial. Businesses should start small with pilot projects to test the feasibility and benefits of AI, then scale gradually based on initial successes and lessons learned. Continuous monitoring and adjustments are essential to optimize AI performance and maximize returns.

Picking the Right Partner

Working with a third-party AI consultant can simplify Gen AI implementation. Experts like Axis Technical Group bring experience and specialized knowledge to navigate technical complexities. They ensure data is clean, relevant, and unbiased, and excel in integrating new AI capabilities with existing systems. Their expertise also helps identify and mitigate ethical and bias concerns, ensuring trustworthy AI outputs.

This article might be of interest, Navigating Generative AI Implementation Challenges.

Gen AI presents a promising investment opportunity for businesses across various industries. By addressing specific business objectives and implementing AI strategically, companies can achieve significant returns. Understanding the potential of an ROI on Gen AI and setting realistic expectations is crucial for maximizing the benefits. Investing in this technology can drive efficiency, reduce costs, enhance customer experiences, foster innovation, and support better decision-making, ultimately leading to substantial business growth and success.