What Is AI in Business?

Digital Marketing - Study Notes:

What is artificial intelligence?

Artificial intelligence (AI) can be defined as the theory and development of computer systems that are able to perform tasks that normally require human intelligence, such as visual perception, speech recognition, decision-making, and translation between languages. It involves computers developing cognitive processes that they can use as a means to make key decisions, such as answering a question.

In a business context, AI can enhance performance by adjusting strategies in real time, such as modifying a pricing model to respond to market fluctuations or selecting targeted communications for specific audiences based on immediate insights about customer behavior. The benefit of AI to organizations is that it aims to create systems with human-like thinking skills, such as the ability to reason, discover meaning, generalize, or learn from experience.

While full sentient AI hasn’t been created yet, there are several task-based automations that were once handled by humans that are now being performed by machines. This, of course, requires inputs from humans to help guide the process to meet your needs. A very simple example is a bank implementing voice and speech recognition into their internet and telephone banking services. This enables customers, for example, to access their bank balance via a voice recognition system rather than talking to a customer service rep.

The efficiency that machine-actioned tasks can bring to businesses is significant and by handling many of these tasks, it frees up time for professionals to make strategic decisions on a course of action for a new strategy. For example, in the finance sector, AI can automate loan approval processes by analyzing applicant data and credit history, reducing processing times and minimizing biases in decision-making.

Benefits of AI to organizations

What are some of the ways that AI can help organizations?

• AI can boost productivity through automation of administrative tasks, such as invoice processing and report generation. This frees up more time for complex and strategic tasks.
• It can also drive efficiency by automating supply chain management and inventory tracking. AI can streamline processes like supply chain management and inventory tracking, making them faster and more accurate. By reducing the risk of stockouts or overstocking, AI-driven efficiency helps organizations reduce waste and respond more effectively to demand.
• And it can unearth insights by analyzing customer data to predict purchasing behavior and enhance customer service. This data-driven insight can lead to improved customer retention and increased revenue. With AI’s data-driven research capabilities, you can develop a more effective marketing approach for your company, and potentially open up new marketing opportunities. Many analytics tools have an automated insights section that will highlight variances in traffic, conversions, and engagement. They will also provide an explanation for what might be the cause of these anomalies, helping you understand new and emerging trends in your data.
• AI can also open new business opportunities through advanced product development and innovation. By harnessing AI, organizations can explore new business models, enter untapped markets, and stay competitive.
• With AI, you can create more personalized campaigns and experiences for your target audience. You can use AI to efficiently craft customized content that will resonate with different audiences and address their needs or preferences. This helps you to attract potential customers and build loyalty with existing customers.
• And finally, it can increase ROI by optimizing resource allocation and minimizing operational costs. This targeted approach not only reduces waste but also maximizes the return on investment.

AI versus human input

Does this mean that the machines are taking over and humans will be rendered redundant? Not at all!

AI offers new ways to complete tedious and repetitive tasks, but there are some tasks that a computer will simply struggle to complete. For example, AI can struggle with effectively teaching new employees or with creativity. While AI-driven tools can assist business professionals across various sectors, these tools still need inputs and direction from you to deliver on your business goals.

Many AI tools do not possess the in-depth contextual understanding of your organization, industry, or specific business processes. This is because they rely solely on the data they are given. Without comprehensive business insights and contextual information, AI tools may not be able to provide meaningful outcomes that align with your strategic objectives. This means you must actively guide these tools to extract the value you need.

For example, in supply chain management, AI tools such as predictive analytics can forecast demand and optimize inventory levels. However, these tools might not account for unexpected disruptions such as natural disasters or supplier issues unless they are fed real-time data or contextual inputs from supply chain managers. Businesses can improve the accuracy of these predictions by integrating qualitative insights – such as upcoming labor strikes or expected delays from a key supplier. They can then mitigate any potential risks proactively.

AI in action

Cutting-edge AI technologies like GPT can generate business reports. And DALL-E can create product designs based on textual descriptions. However, these tools still operate within predefined boundaries set by the data they are trained on. They are highly effective at automating routine tasks, but they lack the nuanced understanding required for complex decision-making, strategic planning, or interpreting business nuances.

As AI evolves, its capabilities in business contexts will expand. However, for now, most applications remain focused on machine learning, which is highly data-dependent and limited by the quality and relevance of the data provided.

To maximize the benefits of AI in business, you must combine these technologies with human expertise. This hybrid approach ensures that AI outputs are not only efficient but also strategically aligned with your business goals and adaptable to real-world complexities.