How to Apply Artificial Intelligence Strategically in Your Organization

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Key Takeaways

  • Effectively harnessing AI will be the key to remaining competitive.
  • Successful implementation of AI starts with preparing your data, defining clear business objectives, and developing a plan for change management.
  • An advisor can help you develop a clear roadmap for applying AI strategically across your organization.

McKinsey reports that 60% of organizations that have adopted artificial intelligence (AI) are already using generative AI, with 40% planning to invest more. Moreover, 75% of their respondents expect generative AI to cause “significant or disruptive change” to the competitive landscape in their industry in the next three years.

Effectively harnessing the power of AI will be key in remaining competitive. However, there are risks to jumping in without a plan. We’ve outlined the three steps to applying AI strategically across your organization.

Prepare Your Data

AI relies heavily on high-quality data. You cannot begin to leverage AI in your organization unless you have a robust data strategy in place. That strategy must be reviewed often and adapted as your organization’s needs evolve.

The framework for any data strategy starts with an assessment. This systematic evaluation of your data assets, infrastructure, and practices provides the opportunity to make informed decisions about data initiatives, prioritize improvements, and establish a data roadmap. In assessing your data landscape, you’ll identify what data you have, where it’s stored, how it’s collected, and who uses it. You’ll also evaluate the quality of your data.

The information garnered from the assessment lays the groundwork for your strategy, which includes five key components.

  1. Data Governance: Establish data governance practices to ensure data quality, security, and compliance. Define roles and responsibilities for data management.
  2. Data Architecture: Decide on the data architecture that best suits your needs. Consider how data will be collected, stored, integrated, and accessed.
  3. Data Analytics and Insights: Determine how data will be analyzed and used to derive actionable insights. This may involve data mining, reporting, data visualization, and advanced analytics.
  4. Data Lifecycle: Define how data will be managed throughout its lifecycle, from data collection and storage to data retention and disposal.
  5. Technology and Tools: Identify the technology and tools needed to support your data strategy. This may include data storage solutions, analytics software, and data integration platforms. Make sure you have the proper security in place to protect your data.

Data quality and accessibility are critical for AI models to generate valuable insights and predictions.

Define Clear Business Objectives

Identify specific business objectives and goals that AI can help address. These objectives should be aligned with your organization’s overall strategy and should contribute to improved efficiency, customer satisfaction, revenue growth, or other key performance indicators. It's crucial to understand what problems or opportunities AI can solve for your organization before you start applying it.

When AI initiatives are not aligned with clear business objectives, there is a risk of pursuing technology for technology's sake. This misalignment can lead to a lack of meaningful outcomes and wasted resources. It becomes challenging to measure the impact and value that AI brings to the organization.

Your ability to effectively measure the impact of your AI initiatives comes from defining measurable key performance indicators (KPIs) before jumping in. This is vital to determining return on investment (ROI). Without this determination, you can’t evaluate whether the AI investment is worthwhile or whether it has a positive impact on the bottom line.

If your business objective is to empower a more productive sales team, you can use AI to streamline their processes. AI-generated email templates, automated email campaigns, and chatbots will allow them to spend more time closing deals and generating revenue—two trackable and measurable KPIs.

Develop a Plan for Change Management

Successful integration of AI into your processes and culture is dependent on user adoption and a carefully thought-out approach to change management.

  1. Clear Communication and Training: Effective communication is essential to inform employees about the purpose of AI adoption, its benefits, and how it will impact their roles. Open and transparent communication helps alleviate concerns and resistance to change. Provide comprehensive training programs to equip employees with the necessary skills to work with AI tools and systems.
  2. Engagement and Involvement: Actively involve employees in the AI adoption process. Seek their input, ideas, and feedback and address any concerns they may have.
  3. Demonstrating Value and Measuring Success: Show the tangible value and benefits of AI to users by providing real-world examples and success stories. Highlight how AI can enhance their work, make tasks more efficient, or improve decision-making.

Creating a supportive and inclusive environment where employees understand the value of AI, are equipped with the necessary skills, and actively participate in the adoption process is vital. There is a general fear of job insecurity today—three out of four Americans believe that AI will reduce jobs.

Work with a Partner

An advisor can help you develop a clear roadmap for applying AI strategically across your organization. Our team at Eide Bailly combines their business knowledge and technology expertise to help organizations of all sizes introduce AI into their business processes in a strategic and methodical way.

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