Business Technology

Impact of AI On Business Analysis

AI has disrupted many industries as well as most roles within these industries and business analysis has not been spared.

The integration of AI into Business Analysis tools has caused massive disruption in the Business Analysis front which has made AI an essential skill for business analysts. The demand for Business Analysis professionals with competence in Artificial Intelligence is on the rise.

The Business Analyst In AI World

Impact of AI On Business Analysis

According to a survey by McKinsey & Company, 87% of companies have AI skill gaps. Consequently, shortage of professionals with AI skills is one major reason why businesses are forced to halt major projects.

Learning Artificial intelligence for business analysis will not only improve your productivity but also equip you with the tools that make business analysis more efficient.

1] Artificial Intelligence

Artificial Intelligence (AI) refers to computers being programmed to operate with the same level of intelligence as that of human beings. Without going into the process of writing code, algorithms are created and trained to classify, analyze, and make predictions from data inputs.

This way, a computer is powered to learn and solve problems like human beings making the decision-making process in businesses fast, more informed, and efficient.

Although there are many approaches to AI, its advancement in two areas, Machine Learning, and Deep Learning has accelerated the field of AI to create a paradigm shift in all areas of the tech industry including business analysis.

With AI permeating every sector of our existence, it is vital to look at AI as a technique that opens up opportunities for improvement of performance by enhancing the speed of execution and facilitating the delivery of targeted services to customers.

The most common form of artificial intelligence is known as narrow AI which is designed to perform very specific tasks for instance SIRI, Google search, or popular self-driving cars.

What are the common applications of AI in business processes?

  • Automation. Automation-driven AI is estimated to have reduced over 9 milling manufacturing jobs in the US alone and created newer roles. AI-enabled tools have enabled the smart use of resources, reduced costs, increased productivity, and created specialized jobs in specific industries.
  • Sales and marketing. AI has transformed the way sales and marketing is undertaken. For instance, AI has enabled marketing professionals to automate many activities and therefore focus on key sales roles like increasing customer satisfaction.
  • Customer service. Enterprises are deploying AI-powered chatbots to ensure that customer service meets individual needs and preferences.

2] Business Analysis

Business Analysis leverages data to identify business needs and recommend solutions that deliver the highest value for these needs. The primary role of business analysis is to consolidate data to facilitate good decision making and help the business to perform better.

AI, on the other hand, helps businesses make the most of data for better and informed decision making. Today, AI-powered tools are critical to business analysis because they are more effective at analyzing large volumes of data and through predictive analysis facilitate fast decision making, strategy building, as well as improved operational efficiency for faster delivery of value to customers.

Business Analyst today, unlike traditionally, is a technology role. AI forms part of the skill-set of a business analyst. A business analyst is a critical player in AI adoption and functionality. Also, his roles are enhanced greatly by the efficiency of AI tools.

AI adoption has expanded the role of a business analyst. He is not only expected to break down complex projects to expand the business to new markets, but business analysts also contribute greatly to a company’s core mission.

Analysts will provide the basic data used in designing algorithms. Additionally, to reduce the risk of flawed and biased data, organizations need to have proper data governance.

3] Impact of AI on Business Analysis and involved Roles

A common question for most analysts is whether AI and Machine Learning can take over the role of a business analyst. The answer is no. AI tools are, in fact, more effective at handling high volumes of complex data.

AI has had a huge impact on business analysis as is evident in its continuously growing applications of robotics, automated bots, digital assistants, and Apps in various industry sectors.

A clever business professional should not only upskill himself  by taking up a Business Analyst Certification Training but also develop good AI related skills that will help in leveraging diverse forms of data to carry out their assignments. Hence the role of an analyst has expanded to undertake tasks traditionally associated with data science.

Some notable impacts of artificial intelligence to the business analyst role include.

  • A major impact of AI is its wide application in banking and finance. Business Analysis tasks have been either partly or fully automated in finance, banking, and portfolio management. In investment banking for instance, “thinking algorithms” are providing technical support to Business Analysts by facilitating automated valuation and book updates.
  • Business Analysis has been made more efficient by AI tools in supporting enterprises to manage the ever-growing volumes of data. Professionals can now use big data to support business decisions.
  • AI empowers BA professionals to get real-time insights from rapidly generated data thus enabling business leaders to respond fast to customer needs.
  • The increased application of AI has reduced the shortage of qualified business analysts while at the same time increasing the productivity of highly skilled analysts who can also complete tasks remotely.
  • Prevention of customer churn, which is a major problem for businesses. AI can be employed to increase customer retention and prevent churn. AI provides a business analyst with a new mechanism like deep learning that does not require a lot of time to retrieve data and establish trends from a large set of data. An analyst with the right AI skills will leverage on the algorithms and use patterns to understand why customer churn is occurring.
  • Influencing purchase decisions and buyer Many factors can be used to influence customer purchase decisions. For instance, understanding customer details like income, gender, and the product or services they currently consume is valuable information for any business that intends to personalize their services. Based on this information, AI can recommend products or services for customers based on data points of the user’s transaction history. Business analysts also use this data to segment users in clusters, establish purchase patterns, and tailor effective recommendations.
  • AI has influenced positively the productivity of analysts conducting quality assurance. It not only facilitates the collection of fast-evolving data and reduces the cost of operation, but it also equips analysts to detect high-risk areas early leading to increased customer satisfaction and profitability.
  • AI has enabled analysts to effectively conduct augmented brand marketing and reputation management. Machine learning is currently being applied to understand a campaign’s target audience. Advertisement campaign analysts can use models that not only capture targeted customers’ texts like social media posts and reviews but also capture images connected to their brands. This allows businesses to measure the sentiments of their audience, track their brand reputation and exposure, to get insights on developing effective campaigns.
Conclusion

Data generated in businesses has become more complex by the day which has forced businesses to rethink their analysis techniques to integrate AI in the business analysis tools that they use.

Two major impacts of artificial intelligence are the shortened supply chain of raw data and enhanced decision making which ultimately improves customer experience.

The effect is that the analyst role is now characterized by a taskforce of automated systems that are useful for advanced analysis.

AI has eliminated many redundant analyst tasks and enhanced the capacity of BAs to focus on higher-value analysis, decision making, as well as innovation tasks. As such, business analysts ought to consider AI as efficient assistants.

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About the author

Ashish Arora

Ashish Arora is a digital marketer and blockchain enthusiast. He is running his many blogs and sharing his 3.5+ years of experience with the online community.

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