Welcome to this introduction of my 5-part series on the transformation of business decision-making using automation. Over the years, information technology has revolutionized the world of business decision-making. What began with basic tools such as electronic calculators and mainframes has evolved into powerful enterprise-wide systems that automate critical business decisions and processes. 

As these systems continue to expand, data was initially considered just a byproduct. However, it soon emerged as a vital resource for businesses. Nowadays, companies leverage business intelligence (BI) reporting to streamline decision-making processes. Additionally, the adoption of robotics and artificial intelligence (AI) has further expanded the possibilities for technology to transform business decision-making. From assisting and enhancing human decision-making to developing fully autonomous agents like smart robots and self-driving vehicles, these capabilities are truly remarkable. 

Join me in exploring the challenges that humans and various forms of information technologies face within the decision-making process. Furthermore, discover the unique advantages each type of information technology brings to the table. Let’s discover the impactful roles of process automation, data-driven decisions, and the game-changing influence of AI on business decision-making in this 5-part article series.

“Automation does not need to be our enemy. I think machines can make life easier for men, if men do not let the machines dominate them.”

John F. Kennedy

1. The Problem-Solving Process: Humans Make Mistakes And Need Tech To Make Better Business Decisions

Decision-making is as old as mankind. To understand Artificial Intelligence’s (AI) impact on decision-making, let’s first explore the 4 basic steps of human problem solving and its challenges. Click here, for an overview of the human decision-making process and the 5 top challenges that humans and business organizations have with making good decisions. To list, key human decision-making challenges include bias, emotions, prone to errors, distractions, and limited information processing capability. Subsequently, the rest of this series will explore the opportunities and the challenges we have with using automation in decision-making. Specifically, this will include process automation, data-driven decision-making, and lastly, AI’s impact on business decisions. See below.

2. Process Automation Technology: Its Value To Best Empower Decision Making In The Age Of AI.

Before AI, businesses used and continue to use traditional automation technology. Traditional process-based automation provides much value to business decision-making. However, it does have major limitations such as its rigid rules-based processing, not able to handle complexity, nor leverage large data sets to name a few. 

For decades, businesses have used rules-based process automation to automate manual tasks and assist with decision-making. As our business environments become increasingly complex and the data becomes overwhelming, AI is starting to appear to be the solution to every problem. But traditional process automation still has its place to support business decision-making. Click here to explore process automation use cases in support of business decision-making and what its limitations are in the age of AI.

3. Data-Driven Decision-Making: Its Enormous Impact And The Truth On Limitations

The explosion of big data has provided businesses with unprecedented access to vast amounts of information that they can use for decision-making purposes. Organizations can now analyze both structured and unstructured data from various sources to identify patterns and trends. Indeed, these correlations and resulting insights were in many cases previously undiscoverable. 

Further, the data-driven decision-making approach enables businesses to respond more accurately and quickly to market changes, customer preferences, competitor activities, and other external factors. On the other hand, there are limitations with a data-driven approach. Specifically, these limitations include underpowered software that cannot handle large data sets and underlying bias that can be present in the data.

Click here to read my article where I explore the impact and limitations of data-driven decision-making. Specifically, this article will touch on data science basics, describe the data-driven decision-making process, its benefits, and its challenges for improving business decision-making in the age of AI.

4. AI Impact On Business Decisions – Know How To Best Apply To Get The Most Benefits

Undoubtedly, AI stands out from other automation forms due to its ability to facilitate decision-making in highly complex environments. Businesses are increasingly harnessing AI for a variety of decision-making situations, reaping significant benefits in the process. Recent advancements in Large Language Models (LLM) and more generalized AI have expanded AI’s potential in augmenting business decision-making beyond traditional automation capabilities. Furthermore, AI, when combined with robotics, can operate autonomously in both decision-making and physical tasks.

So AI increasingly can replace or enhance both human and lower forms of automation to automate, augment, or support decision-making. Additionally, it can do this in use cases that are simple, complex, and even chaotic. So click here to get started on how you can apply AI to business decision-making. And most importantly, use better decision-making to improve business execution.

5. AI Impact On Business Decisions – Know AI’s Unique Challenge To Overcome Its High Number Of Weaknesses

However, AI still has many weaknesses when it comes to supporting business decision-making. Specifically, AI challenges include transparency, it can be biased, uses a lot of computing power, privacy concerns, and it is not morally responsible to name a few.  In spite of AI decision support being a unique challenge to overcome, it is definitely worth pursuing. At the same time it is critical that you know the weakness of AI in supporting decision-making, Click here to explore the 11 weaknesses in AI with providing automation support for business decision-making.

“The real danger is not that computers will begin to think like men, but that men will begin to think like computers.”

Sydney J. Harris

For more on our Series on AI Impact On Business Decisions, see links below:

• The Human Problem-Solving Process – Part 1
• Process Automation – Part 2
• Data-Driven Decision-Making – Part 3
• AI Impact on Business Decisions – Opportunities – Part 4
• AI Impact on Business Decisions – Limitations – Part 5

For more on problem-solving, see Unvarnished Facts’ A Superior Problem Solving Process: How To Produce Better Results for more details. Also, see SC Tech Insights articles on decision science, information technology, data, and AI.