An artificial intelligence strategy or AI strategy is a plan that includes a set of goals and objectives, and actions and guidelines that describes how an organization will use artificial intelligence to achieve its organizational goals and objectives, address existing problems and issues, or discern and maximize opportunities.
Developing and Implementing an AI Strategy: Understanding and Mastering the Potential and Capabilities of Artificial Intelligence
Overview
Developments in the field of artificial intelligence have expanded its practical applications and made resulting technologies or products more accessible to the public. Organizations are now building capabilities for using AI in a manner that is similar to how technologies like the internet became an integral part of day-to-day operations.
A specific AI strategy holds immense potential for various applications in different businesses across different industries and sectors. It can revolutionize sales and marketing through personalized recommendations and sales process automation while improving customer service and after-sales services through chatbot support.
Financial services providers can use artificial intelligence to automate underwriting, detect fraud, and optimize investment strategies. Relevant technologies can be used in the manufacturing sector to optimize production processes, automate tasks, improve quality control, reduce operational costs, and enable predictive maintenance.
The agricultural sector has been using AI to implement precision agriculture and automate certain processes in farm operations while the thee healthcare sector and the field of medicine have exploring how artificial intelligence can enhance diagnostics, predict disease progression, and enable precision and personalized medicine.
An AI strategy is fundamentally a plan that explains how an organization will benefit from artificial intelligence and provides details on how it will use relevant artificial intelligence technologies, techniques, and products to complement or improve further its overall strategy and meets its organizational goals and objectives.
Notable Examples
The examples above demonstrate that the emergence of various AI products and access to AI technologies and tools have created novel use cases that can benefit and revolutionize organizations and even an entire industry or sector. A particular organization can develop its AI strategy based on identified use cases or applications.
Below are some examples of AI applications:
• Processes Automation: An artificial intelligence system can be used to automate repetitive tasks or certain operational processes. More specific examples include automating the sales process or specific steps in the manufacturing process. Automation reduces errors and promotes output quality, enables people to focus on other more important tasks, and improves overall organizational productivity.
• Customer Experience: It can also be used to personalize customer experiences through data-based product recommendations and client servicing. AI can also make customer support operations more efficient through the use of chatbots built on an organizational knowledge base. Improving customer experience is essential to enhancing customer satisfaction, maintaining relationships, and encouraging repeat sales.
• Predictive Analytics: Organizations can also capitalize on the predictive capabilities of artificial intelligence to analyze large datasets or big data to determine patterns, trends, and insights that can help in making data-driven predictions and decisions. This includes demand forecasting, predicting customer behavior, improving the supply chain, optimizing inventory management, and anticipating maintenance needs.
• Assessing Risks: AI can also equip an organization with the ability to assess risks relevant to its business using its predictive and analytical capabilities. An AI system can assess risk factors, perform regulatory compliance checks, and flag potential violations. This helps organizations in industries such as finance, healthcare, and legal services to manage risks, ensure compliance, and avoid penalties.
• Reducing Expenditures: The analytical capabilities of AI can also help make an organization more cost-efficient. Some AI algorithms and models have been used to reduce energy consumption. The simplification of certain processes through automation can also lessen costs associated with redundancies or process inefficiencies. AI can also be used to determine other opportunities for cost savings.
• Idea Generation: Advances in natural language processing and large language models have brought forth generative artificial intelligence applications with capabilities to communicate with human users. Services like ChatGPT from OpenAI, Bing Chat from Microsoft, or Gemini from Google can help in brainstorming new ideas for products, marketing activities, and operational processes.
Elements of the Strategy
It is important to align a specific AI strategy with the overall strategy of an organization. The same strategy should also pinpoint areas where artificial intelligence can be used to create value. An effective AI strategy should outline and describe how relevant technologies and techniques or related products can be used in an organization.
Below are the elements of an AI strategy:
• Purpose, Goals, And Objectives: This involves stating the purpose of AI in the organization and how it fits into its overall strategy. It is also important to outline and describe the specific things it wants to achieve with AI or how it will help the organization meets its organizational goals and objectives.
• Implementation Roadmap: An organization should also be able to describe how it will implement its AI strategy. This centers on determining resource requirements needed to support the strategy and acquire relevant capabilities. Examples of these resources include technologies or equipment and tools, talent, and capital.
• Governance and Ethics: The strategy should also provide a framework or a set of guidelines for the responsible or safe and ethical use of artificial intelligence. This includes considerations for data privacy protection, departmental and organizational accountability, and alignment with relevant laws or regulations.
• Risk Management Plan: Another critical element of an AI strategy is a specific risk management plan that includes an outline and description of potential risks that might arise from using artificial intelligence, the possible impact of these risks, and the specific actions aimed at eliminating or mitigating these risks.
• Monitoring and Evaluation: It is also important for an AI strategy to have mechanisms to monitor the progress of specific initiatives, evaluate their impacts, make needed adjustments to ensure alignment with the overall organizational strategy, and measure how the strategy is meeting its stated purpose, goals, and objectives.
The aforementioned elements of an AI strategy also correspond to the principles of an effective AI strategy. Furthermore, in consideration of their collective role in developing and implementing the strategy, an organization needs to be reminded that it needs to have a clear understanding of how AI can help achieve organizational goals and objectives, solve existing problems or issues, improve the business, or advance its interest.
An organization should also examine its entire value chain to determine the areas where AI can be applied and bring forth additional value. These include looking for opportunities for automation, enhancing customer experience, optimizing or reducing costs, making better decisions based on data, assessing risks, and new idea generation.
The implementation of an AI strategy can make or break its relevance and value. It is important to have the needed resources to build capabilities in deploying relevant artificial intelligence technologies, tools, and products. This starts with a clear assessment of the existing organizational capabilities. Implementing an AI strategy can be resource-intensive. It is important to determine if the potential benefits outweigh its costs.