ARTICLE
10 September 2024

A Primer For Leveraging AI To Drive Growth

The Artificial Intelligence (AI) revolution is transforming industries, enabling businesses to increase profitability, innovate, and drive efficient operations.
United States Technology
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The Artificial Intelligence (AI) revolution is transforming industries, enabling businesses to increase profitability, innovate, and drive efficient operations. As technology advances, it's imperative for middle market executives to understand and embrace AI to remain competitive and drive sustainable growth. Organizations looking to adopt AI later run the risk of being left behind.

One of the first priorities for executives is to align AI opportunities with the organization's business objectives. While there are an almost infinite variety of AI benefits, selecting the ones that best align with the organizational priorities, will ensure the best fit and highest probability for success. This starts with selecting AI use cases that create a clear return on investment (ROI) in an acceptable time. Creating opportunities for near term measurable returns rather than "moonshots" increases commitment and confidence for future AI projects.

In early stages, executives should focus on driving efficiencies or in areas of measurable impact on revenue and profitability. Building confidence in the team, in AI, and value creation will increase future commitment. Potential opportunities could include analyzing recurring product or service defects, analyzing marketing programs for engagement and click throughs, or customer service enhancements through chatbots. Setting measurable goals and key performance indicators (KPIs) is essential to track progress and demonstrate the value of AI investments.

Quality AI systems are as good as the data they utilize.

For middle market companies, it is crucial to have a robust data management strategy. Executives must ensure that the organization has access to high-quality, relevant, and timely data. This involves establishing strong data governance practices to maintain data integrity, accuracy, and privacy. It may also include engaging experienced data analysts to improve and structure data sets.

Investing in the right infrastructure and tools to collect, store, and analyze data is also necessary. This infrastructure should be scalable and secure, enabling the company to grow its AI capabilities over time. Moreover, companies must comply with data protection regulations, ensuring that customer data is handled ethically and legally.

Choosing and investing in the right technology is pivotal to proper outcomes.

While executives don't always have the time to stay informed about the latest AI trends and technologies, having either an employee or advisor that understands the latest trends and technologies is vital. Many organizations are focused on the latest technologies such as chatbots and generative AI, however, there are many other forms of AI such as robotic process automation (RPA), embedded AI (included in many mainstream applications), computer vision, predictive analytics, robotics, and many others.

For many organizations a "crawl, walk, run" strategy is often the best. Starting with smaller, less complex AI projects that can deliver quick wins and provide valuable learning experiences can build confidence while limiting risk. As the organization becomes more comfortable with AI, it can gradually scale up its efforts and tackle more ambitious projects.

Determining whether to "walk alone" or partner with an experienced AI advisor / partner is a key consideration for success. While in the short term it may be less expensive to house these projects with internal staff, a partner / advisor can accelerate success, build confidence, and increase the overall return by avoiding many issues incurred with "brute force" learning.

Implementing AI is not only a technological shift but also a cultural one.

Executives must foster a culture that supports continuous learning and innovation. This may involve recruiting new talent with expertise in AI, machine learning, and data science. Additionally, companies should invest in training programs to upskill existing employees, enabling them to work effectively with AI technologies. In addition, creating a culture of learning during difficult or "failed" projects is critical to longer term organizational success.

Proactively understanding and addressing organizational risks is critical to success. AI brings risks of bias, "hallucinations," fear of job loss and potential for market impact and even legal risks. Organizations must establish secure environments to protect confidential data, and policies and procedures for responsible AI usage, ensuring that AI systems are fair, accountable, and respectful of user privacy.

Partnering with key legal advisors to understand the implications of data privacy regulations like the General Data Protection Regulation (GDPR) and the California Consumer Privacy Act (CCPA) will assist with ensuring the right legal protections and compliance. Compliance with these and other industry-specific regulations is not mandatory.

AI presents significant opportunities for middle market companies to thrive and grow, but it also requires a deliberate and strategic approach. By focusing on these above topics, executives can steer their organizations towards a rewarding AI outcome. As they chart this course, they must remain agile and receptive to change, leveraging key partners to thrive in this dynamic and evolving business environment.

With a deep understanding of AI's potential and its pitfalls, Marcum Technology is the ideal guide to help your organization through this digital revolution. Contact Marcum Technology to embark on a path that not only navigates the intricacies of AI but also capitalizes on its vast opportunities for sustainable success.

The content of this article is intended to provide a general guide to the subject matter. Specialist advice should be sought about your specific circumstances.

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