Artificial intelligence (AI) is a powerhouse of transformation. The automation of tasks traditionally reliant on human intelligence is having far-reaching impacts, creating new opportunities for innovation and enabling businesses to reinvent their operations. By empowering machines with the ability to learn, reason, and make decisions, AI is impacting nearly every industry, from manufacturing to hospitality, healthcare to academia. Without an AI strategy, organizations risk missing out on the benefits AI can bring.
An AI strategy helps organizations address the complex challenges associated with AI implementation and define its goals. Clearly defining objectives and plans, whether that be deeper data analysis, optimizing business processes, or improving customer experience, ensures that AI adoption is aligned with broader business goals. This alignment is essential to derive meaningful value from AI and maximize its impact. A successful AI strategy also provides a roadmap for addressing challenges, building the necessary capabilities, and applying AI strategically and responsibly into the fabric of your organization.
Organizations that make the effort to understand AI and leverage its power now will thrive in the future. With a robust AI strategy, these organizations can navigate the complexities of AI integration, quickly adapt to technological advancements, and optimize processes, operational efficiency, and overall growth.
What is your AI strategy?
An artificial intelligence strategy is simply a plan to integrate AI into your organization to align with and support your broader business goals. A successful AI strategy should act as a roadmap for this plan. Depending on your organization's goals, your AI strategy might outline steps to effectively use AI to extract deeper insights from data, increase efficiencies, build better supply chains or ecosystems, and improve talent and customer experiences.
A well-developed AI strategy also helps guide technology infrastructure, ensuring that your company has the hardware, software, and other resources needed to implement AI effectively. Technology also evolves rapidly, so your strategy should enable your organization to adapt to new technologies and industry changes. Ethical considerations such as bias, transparency, and regulatory concerns should also be addressed to support responsible deployment.
As artificial intelligence continues to impact nearly every industry, a well-thought-out AI strategy is essential — one that can help organizations unlock their potential, gain a competitive advantage, and achieve sustainable success in an ever-changing digital age.
Read more about IBM's AI Ethics Governance Framework
The benefits of a successful AI strategy
Developing an AI strategy offers many benefits to organizations working to integrate artificial intelligence. An AI strategy helps organizations intentionally leverage AI capabilities and align AI initiatives with overall business goals. An AI strategy provides a compass for making meaningful contributions to the success of an organization. It helps stakeholders select projects that will provide the greatest improvement to critical processes, such as productivity and decision-making, and to the bottom line.
More specifically, an AI strategy outlines the steps that will enable AI projects to smoothly translate ideas into effective solutions. It also requires organizations to make key decisions about data, talent, and technology. A well-crafted strategy provides a clear plan for managing, analyzing, and leveraging data for AI initiatives. It also determines whether an organization needs to develop, attract, or retain talent with relevant skills in data science, machine learning (ML), and AI development. It also guides the procurement of the hardware, software, and cloud computing resources required to ensure effective AI implementation.
In essence, a successful AI strategy is essential and serves to support business objectives, drive prioritization, optimize talent and technology choices, and ensure the organizational integration of AI to support organizational success.
Steps to building a successful AI strategy
The following steps are typically used to develop an effective artificial intelligence strategy:
Explore the technology
Understand the various AI technologies, including generative AI, machine learning (ML), natural language processing, and computer vision. Research AI use cases to understand where and how these technologies are being applied in relevant industries. List the problems that AI can solve and the benefits it can provide. Note down the departments that use AI, how they do it, and the obstacles they face.
Evaluation and Discovery
Understand the organization, its priorities, and capabilities. Review the size and strength of the IT department that will implement and manage AI systems. Interview department heads to identify potential problems that AI could solve.
Define clear goals
What problem does your organization need to solve? What metrics do you need to improve? Rather than assuming AI is always the answer, choose business objectives that are important to your business and that AI has a proven track record of successfully solving.
Identify potential partners and vendors
Find AI and ML companies operating in your industry. Make a list of potential tools, vendors, and partnerships and evaluate their experience, reputation, pricing, etc. Prioritize procurement based on the phase and timeline of your AI integration project.
Create a roadmap
Develop a roadmap that prioritizes early wins that deliver value to the business. Select projects based on identified practical needs. Determine what tools and support you need and organize them based on what is most important to your project. Specifically:
- data: Develop a data strategy by determining whether new or existing data and datasets are needed to effectively drive AI solutions. Establish a data governance framework to effectively manage data.
- algorithm: Algorithms are the rules or instructions that enable a machine to learn, analyze data, and make decisions. A model represents what has been learned by a machine learning algorithm. These tasks require expertise to manage effectively, so you decide who will deploy the algorithms and design, develop, and validate the models.
- infrastructure: Decide where you will host your AI systems and how you will scale them: on your own infrastructure or on a third-party platform.
- Talent and outsourcing: Assess readiness and skills gaps within your organization to implement AI initiatives. Determine whether a talent pipeline exists to fill roles such as data scientists and developers, or if skills can be developed in-house through training. Also assess whether certain tasks such as deployment and operations need to be outsourced.
Presenting an AI strategy
Present your AI strategy to stakeholders and ensure it aligns with business goals. Get buy-in for the proposed roadmap. Clearly communicate the benefits, costs, and expected outcomes. Secure the necessary budget to execute the strategy.
Initiate training and encourage learning
Start upskilling your AI team and hiring talent with the right AI expertise. Keep your team up to date on cutting-edge AI advancements and encourage them to explore innovative ways to solve problems.
Establishing ethical guidelines
Understand the ethical implications of your organization's responsible use of AI. Commit to ethical AI initiatives, comprehensive governance models, and practical guidelines. Regularly monitor AI models for potential bias and implement fairness and transparency practices to address ethical concerns.
Evaluate and adapt
Keep up with the rapid development of new products and AI technologies. Adapt your organization's AI strategy based on new insights and emerging opportunities.
Following these steps can create a powerful guide for integrating AI into your organization, which will enable your business to better capitalize on the opportunities in the dynamic world of artificial intelligence.
Common obstacles to building a successful AI strategy
There are various issues that can get in the way of building and implementing a successful AI strategy. To move forward effectively, you need to assess early on the issues that may hinder the process and address them accordingly.
Insufficient data
Where and how is your data actually stored? AI models are highly dependent on robust datasets, so insufficient access to relevant, high-quality data can undermine the strategy and effectiveness of your AI applications.
Lack of knowledge about AI
Lack of awareness about AI's capabilities and potential applications can lead to skepticism, resistance and misinformed decision-making, which undermines the value of the strategy and impedes the integration of AI into organizational processes.
Strategy Mismatch
If AI initiatives aren’t tightly aligned with an organization’s goals, priorities, and vision, they may be wasted efforts, lack support from leadership, or fail to demonstrate meaningful value.
Talent shortage
AI initiatives require experts to effectively develop, implement, and manage them, and a shortage of AI talent, such as data scientists and ML experts, or current employees' resistance to upskilling can impact the viability of your strategy.
AI Strategy and IBM
Recent developments in artificial intelligence (AI) demonstrate the scale and power of this technology's impact on business and society. However, the scalability of AI technologies can have a profound impact on both business and society, and companies must determine how to build and govern these systems responsibly to avoid bias and error. As organizations apply machine learning and automation to workflows using diverse datasets, it is critical that they have the right guardrails in place to ensure data quality, compliance, and transparency within their AI systems.
IBM helps you put AI to work today by focusing on areas of your business where AI can deliver real benefits quickly and ethically. Our rich portfolio of business-grade AI products and analytics solutions are designed to lower the barriers to AI adoption and help you establish the right data foundation while optimizing outcomes and responsible use.
Enterprises around the world turn to IBM Consulting™ as a partner in their AI transformation efforts. As a leading AI consulting firm, we leverage our proprietary IBM watsonx technology and an open ecosystem of partners to deliver any AI model, on any cloud, with ethics and trust, to enhance the impact of AI development and cloud technologies in business transformation.
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