The Value of AI in Business
Developing an AI strategy for your business.
Most business leaders understand that artificial intelligence will impact their business in some way. As the hype of AI subsides, business leaders need to revert to best practices and develop an actual strategy for utilizing AI for their business. Like any well-designed strategy, an AI strategy needs to consider the organization's size, the company's resources, the financial capacity to fund any AI initiative and the likely ROI.
The AI strategy for the organization should ideally identify how AI will be able to create new value for the various stakeholders. The stakeholders to be considered should include customers, employees, vendors, and shareholders. An AI roadmap for the incorporation of AI into the business should be developed based on the value that can be created relative to the cost.
The AI strategy that is developed should be a subset of the overall corporate strategy. The alignment between the two strategies is essential to ensure meaningful and relevant value creation. The AI strategy should not only help achieve the corporate strategy faster but should be able to create new value for stakeholders that was previously not conceived.
This report provides insights on how AI in business is used to create new value and the high-level considerations when developing a strategy for using AI in your organization.
Global adoption rates of AI in business
It is worthwhile noting the global trends for AI adoption. The most recent figures from an IBM survey in 2024[1] reveal that enterprise deployment of AI tools has increased to approximately 42%. An additional 40% were experimenting and exploring AI tools but had not deployed tools yet. The biggest challenges to deployment include limited AI skills and expertise (33%), too much data complexity (25%), and ethical concerns (23%).
The IBM survey identified that early adopters are leading the way, with 59% of responding enterprises already working with AI intend to accelerate and increase investment in the technology.
The number of use cases for AI in business has driven the adoption rates. The surveyed enterprises identified key areas of business where AI was either being deployed or was being investigated for future consideration:
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- Automation of IT processes (33%)
- Security and threat detection (26%)
- AI monitoring or governance (25%)
- Business analytics or intelligence (24%)
- Automating processing, understanding, and flow of documents (24%)
- Automating customer or employee self-service answers and actions (23%)
- Automation of business processes (22%)
- Automation of network processes (22%)
- Digital labor (22%)
- Marketing and sales (22%)
- Fraud detection (22%)
- Search and knowledge discovery (21%)
- Human resources and talent acquisition (19%)
- Financial planning and analysis (18%)
- Supply chain intelligence (18%)
Most organizations cited the ease of use of AI tools and the need to reduce costs and automate processes as the primary drivers for AI adoption in the workplace.
A variance exists between different countries in the deployment rates of AI. Survey results identified India and the UAE as leading deployment of AI in business while countries like France, Australia and Spain were still in the exploratory stage. Countries like the UAE had a government that was early in understanding the potential of AI and released an AI strategy that a dedicated department would execute. The economic value of AI is potentially a game changer for many countries, and it becomes clearer why countries like India have also led in the deployment of AI. In a report by McKinsey and Company, 63 generative AI use cases were identified across 16 business functions that were estimated to generate value in the range of $2.6 trillion to $4.4 trillion in economic benefits annually when applied across industries.[2] The increase in labor productivity and reduced costs from generative AI can potentially generate substantial economic value. McKinsey estimates the total economic value of generative and nongenerative AI to be between 17.1 to 23.6 trillion dollars.
Generative AI holds the potential to transform the landscape of an entire organization by enhancing function-specific applications and revolutionizing the way internal knowledge management systems operate. Its advanced natural-language processing capabilities allow employees to interact with the system using conversational queries similar to those they would pose to a colleague. This interaction facilitates a continuous dialogue, granting teams swift access to pertinent information. Consequently, this accelerates the decision-making process and aids in the formulation of more effective strategies, thereby contributing to the overall value of the organization.
The 63 use cases identified in the McKinsey report identified the potential economic impact by industry and by functional areas:
In another research report[3], organizations that adopted AI could show both decreases in costs and increases in revenues. The results across all functional areas that had deployed AI suggest that organizations can realize a tangible and measurable bottom-line improvement:
[1] IBM Global AI Adoption Index 2023. https://www.multivu.com/players/English/9240059-ibm-2023-global-ai-adoption-index-report/
[2] The economic potential of generative AI: The next productivity frontier – McKinsey & Co. ,February 2024
[3] Nestor Maslej, Loredana Fattorini, Raymond Perrault, Vanessa Parli, Anka Reuel, Erik Brynjolfsson, John Etchemendy, Katrina Ligett, Terah Lyons, James Manyika, Juan Carlos Niebles, Yoav Shoham, Russell Wald, and Jack Clark,
“The AI Index 2024 Annual Report,” AI Index Steering Committee, Institute for Human-Centered AI, Stanford University, Stanford, CA, April 2024
Selecting the right AI tools
The number of users of AI tools is expected to more than double over the next five years. A report published by Statista identifies the global number of users increasing from 314 million in 2024 to 729 million in 2030. 
The number of AI tools is also increasing rapidly, making it challenging to pinpoint the best tools for your business. When developing your AI strategy, you will be able to more accurately identify your needs and the types of tools best suited to achieve your objectives by taking a methodical approach to identify the use cases for each functional area. The steps to follow may look like the following:
- Identify the role of AI within the organization. Is there a strategy? Do stakeholders understand and accept the strategic value of AI in helping the business reduce costs and increase revenue?
- Form a cross-functional AI team. Once AI is identified as having importance to the organization, the next stage is to set up a governance team based on cross-functional team members. This team will help drive changes and ensure value creation is delivered for various stakeholders.
- Allocate an AI researcher to the team. The technology is evolving quickly, and new tools are emerging rapidly. The allocation of a researcher will help ensure the most current tools are made available to the team, and the feature sets are known. Often, the use cases can not be developed without first knowing what the tools actually do.
- Workshop on how AI can benefit a functional area. Collaborating with functional team members is important to develop the use cases. This is the time to reimagine customer journeys and internal processes to identify ways to enhance the experience, reduce costs and increase revenue.
- Procure tools to match your requirements. When procuring tools, it's important to take into consideration ease of use, the underlying AI technology, and the employee training required.
- Implement a pilot to verify the results. The objective should be to find an AI tool that you can pilot and see if you get the desired results.
AI technologies are rapidly becoming pivotal for future value creation for most industries. By taking these steps, organizations can ensure they don't get left behind.
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