Can Gen AI Live Up to Its Promise? How to Get Started

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Maximizing ROI on Gen AI is an ongoing process. Success requires continuous monitoring, evaluation, and adjustment.

The last several years have been a rollercoaster for IT departments – from a post-COVID boom in tech valuations and increased spending to massive layoffs across tech companies and investors scrutinizing the ROI of tech investments. Other difficult circumstances like inflation and high interest rates have put further limitations on already financially and resource-strained IT departments. These circumstances have made continued innovation difficult, and IT leaders are searching for new ways to capitalize in the current environment.

Is Gen AI the answer? Since ChatGPT exploded onto the scene in 2022, many in the tech industry have predicted how the vast capabilities of Gen AI can bring significant efficiency and productivity boosts while helping organizations cut costs. If the promise of AI pays off, it will enable IT departments to do more with less and more quickly.

A recent report corroborates the drive for AI, finding that 90% of business and IT leaders across a broad range of industries agree that Gen AI can improve the development and automation of data, application, and process integrations. Indeed, McKinsey research suggests that Gen AI could enable automation of up to 70% of business activities across almost all occupations by 2030. As a result, AI spending is predicted to reach $100B in the U.S. and $200B globally by 2025.

However, the rush to innovate imposed on business leaders by the fast pace of technological change and the need to stay competitive can impede the quality of an organization’s Gen AI strategy and outcomes. In an effort to create the next big thing or make significant breakthroughs with the likes of OpenAI or other Gen AI tools, business leaders often forgo crucial planning and careful step-by-step considerations for their organizations when implementing AI. This can cause inadequacies that lead to risks like unfeasible products and wasted time and capital. It can also cause privacy and bias issues, which can result in grave legal implications.

Unlocking optimal and early business value with Gen AI hinges on effectively orchestrating its components. Think of it as conducting a symphony of AI technologies — integrating data, automating workflows, and ensuring seamless customer experiences. By mastering this orchestration, businesses can drive innovation and optimize processes.

To achieve this, organizations need to execute strategic, thoughtful processes throughout their AI journey – from initiation to implementation and everything in between.

See also: Bridging the Gap: Scaling GenAI for Real Business Growth & Impact

Gen AI investments: Expected benefits drive growth

AI will play a critical role in future business strategies. The automation and optimization AI can bring will foster data-driven decisions and new business models. Organizations can use AI to deliver innovative solutions tailored to a company’s unique setup for proper assessment, prioritization, and implementation.

There are practical use cases of Gen AI across industries. For example, it can be used to generate code, a foundation of the majority of tech innovation today, reducing the time developers spend on routine tasks and speeding up innovation. Tech companies can also use Gen AI to automate the generation of API documentation, a vital tool for developers that facilitates effective communication between software modules, ensuring consistency and a faster and easier software development process. This spills to other industries as well. A retail company, for example, might use Gen AI to optimize inventory management, while a healthcare organization might use it to predict patient outcomes based on medical records.

Considering this, it’s no wonder recent research shows 88% of all C-suite respondents see Gen AI as a game changer and are broadly investing in applications that use it, driven by the potential of increased productivity (44%), sales and revenue growth (40%), and improved customer experience (39%). More than half of the C-suite (55%) view Gen AI as “very important” for the integration of data, applications, and processes and are currently implementing it.

Business leaders are also seeing the value of AI agents for their businesses – nearly half (47%) found that chatbots and virtual assistants significantly improve workforce productivity and customer experience. This is in large part due to the customization of AI agents to specific business needs and training them on the organization’s proprietary data, which helps mitigate some of the security stressors for organizations.

See also: Beyond the Euphoria: Responsible Use of GenAI

Maximizing ROI on Gen AI investments in a constrained budget environment

Maximizing ROI on Gen AI is an ongoing process. Success requires continuous monitoring, evaluation, and adjustment to organizations’ business needs and the environment. Companies need to engage in strategic planning and develop efficient roadmaps to avoid roadblocks and other major risks that could impede their success trajectory.

Here are some crucial actions to implement:

  • Planning and Roadmapping: Organizations should engage in strategic planning and efficient, plausible roadmap creation. It’s important to gather relevant use cases across the organization, including all C-suite members and business divisions.
  • Value and Cost Evaluation and Performance Monitoring: Prioritizing Gen AI use cases and conducting AI pilots before officially implementing is crucial to assess value, cost, and technical feasibility. Uninterrupted performance monitoring is imperative via both quantitative and qualitative measures, such as accuracy and precision, track performance metrics like latency and scalability, and benchmarking. Feedback from end users and stakeholders can provide valuable insights and ideas for improvement.
  • Responsibility: Organizations should responsibly leverage the transformative capabilities of Gen AI. This includes ensuring the reliability and fairness of AI outputs and mitigating bias. Insufficient effort on this front at an early stage can create immense losses at a later stage, including to a business’s reputation. For example, leveraging a Gen AI governance framework lets organizations assess their maturity and compliance while identifying areas of strength and improvement to bolster AI governance. This breaks the “do now, fix later” cycle by giving organizations a genuine guide to getting it right the first time.
  • Talent: A large part of investing in Gen AI is investing in your workforce. To leverage the transformative capabilities of Gen AI, organizations need the right talent to support implementation and execution. Skilling your current workforce saves time and cost. Recent research found that 80% of business leaders plan to reskill employees to use AI in the workplace.

Companies attuned to significant technological changes understand the importance of adaptability and the integration of the latest technologies to maintain competitiveness. Confronted with limited budgets, they focus on reordering their priorities to align with their objectives and seek intelligent strategies to maximize the utilization of their existing resources.

Gen AI can be utilized across a wide range of business operations. It has the potential to improve data quality, enhance content production, streamline workflows, and deliver personalized experiences at scale. This empowers organizations to innovate by freeing up their teams to work on strategic initiatives and explore new opportunities, accelerating the development of new features and products and, ultimately, maximizing the business value of AI.

Matt McLarty

About Matt McLarty

Matt McLarty is Chief Technology Officer at Boomi, which helps organizations around the world to thrive in the digital age. He is an active member of the worldwide API community and has led global technical teams at Salesforce, IBM, and CA Technologies after starting his career in financial technology. Matt has co-authored books for O'Reilly, co-hosts the API Experience podcast, and is co-author of the new book Unbundling the Enterprise from IT Revolution.

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