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In today’s business landscape, AI and automation are increasingly important. Over 50% of organizations plan to incorporate them in 2023. Implementing AI comes with opportunities across different business units. Yet at the same time, it provides challenges that companies must address.
Operations: AI can optimize resource allocation and improve performance in operations. However, businesses need to make their AI systems compatible with existing infrastructure. It is crucial for companies to realize that AI can make mistakes, so they should focus on eliminating them.
For instance, Uptake worked closely with customers to integrate their AI software into their vehicles’ existing systems. The company made sure its predictions were reliable and did not interfere with vehicle performance or safety.
Customer service: Finding the right balance between automation and human interaction is crucial when it comes to using AI in customer service. Virtual assistants should provide quick and relevant responses. But customers must be able to access human representatives when needed. Regular monitoring of customer queries and feedback is also necessary for good AI system performance.
A prime example of this is Volvo’s early warning system. It involved collecting and analyzing large amounts of data from various sources — namely, car sensors and customer feedback. Additionally, the company checked that the system’s predictions were accurate and timely, thus avoiding compromising customer trust in their vehicles.
Related: 5 Tips for Integrating AI Into Your Business
Sales and marketing: Incorporating AI into sales and marketing presents several challenges. Firstly, AI-powered chatbots must be effective in handling customer inquiries without causing frustration. Secondly, personalized recommendations should be based on relevant and ethical data. Finally, implementing lead scoring and predictive analytics requires careful consideration of customer sentiment.
For example, Amazon trained its algorithms to effectively understand customer preferences and patterns. Dynamic pricing required continuous monitoring to ensure prices were appropriate.
Finance: To implement AI in finance, businesses must comply with regulations and ethical standards. It is important to ensure that AI systems are transparent and can be explained to customers and stakeholders.
A case in point is JPMorgan. They made sure their AI initiatives did not violate legal or ethical boundaries (discrimination or biased decision-making). The company worked closely with regulators and stakeholders and thereby manages to achieve transparency and explainability of their AI systems.
Technology solutions to enhance AI-based business automation
While AI is a powerful tool for business automation, it is not the only technology that can be used to optimize processes. By combining AI with other technologies, companies can unlock even greater potential for efficiency and innovation.
Cloud computing: Cloud technology enhances AI-powered applications. It allows businesses to store and access large amounts of data, providing the scalability and flexibility needed for AI to function at its best.
With cloud computing, companies can also save costs by avoiding the need for expensive on-premise infrastructure. Combining AI with cloud computing, you gain real-time insights from their data, improve decision-making and automate tasks more efficiently.
Related: 4 Ways You Should Be Using Cloud Computing to Scale Your Business
Digital twins: When used in conjunction with AI, digital twins can provide even greater value for companies’ automation. AI algorithms analyze data collected by digital twins to identify insights, and as a result, they get further ideas for optimizing business processes.
Consider a fashion retailer that has a digital twin of a brick-and-mortar store. Sensors are used by a virtual twin to gather information on consumer behavior (foot traffic, product interactions and sales transactions.) While this data is being processed, AI algorithms look for patterns to improve the store’s layout and product placement.
Digital process automation (DPA) platforms: Such platforms help streamline complex processes by integrating AI with workflow automation, data integration and analytics. This not only reduces errors but also frees up employees to focus on more important tasks.
Digital process automation platforms can be utilized in various industries such as banking for loan approval processes or in insurance for automating claims processing. By using DPA platforms in combination with AI, businesses can make better decisions, achieve greater efficiency and reduce costs.
AI isn’t enough
In the world of business automation, AI is like a trusty hammer in a builder’s toolkit. It’s a versatile and powerful tool that can get the job done. But it’s not the only tool available.
By incorporating cloud computing, digital twins and DPA platforms into the mix, companies can add other specialized tools to their arsenal, thereby unlocking new levels of efficiency and innovation.
While there may be challenges in implementing these technology solutions, the rewards they offer are too great to ignore. So, just as a builder wouldn’t rely solely on a hammer to build a house, businesses shouldn’t rely solely on AI for their automation needs.
Related: The Perfect Blend: How to Successfully Combine AI and Human Approaches to Business
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