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  • Writer's pictureGemma Walton

How Has Business Analysis Changed Since The Introduction Of Artificial Intelligence

Updated: Apr 25

With the rise in technology, the world has been changing rapidly, and that is also the case for business analysis. Business analysts today have more tools than ever before to work with thanks to the usage of AI and Machine Learning technologies.

The innovations in AI, machine learning, and business analysis will ensure future experts in this field need retraining. The full potential of artificial intelligence will be realised in only AI-related projects if business analysts are committed to keeping up and learning new skills. The current state of AI technology does not permit for the implementation of ambitious projects that would totally transform how businesses do business.

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To realise the value of AI within an enterprise, business leaders need to understand how AI works, where AI technologies can aptly be used within their businesses, and where they cannot - a difficult proposition given the rapidly evolving state of AI and its many use cases. As explained in this deep dive into adopting AI in business, capturing value from many AI technologies requires companies to tackle challenges related to people, processes, and technology. These examples show that future professionals in the field of business administration will need training on understanding how AI works, and how they can leverage it to make data-driven decisions for their businesses, as well as on integrating AI for the automation of certain processes.

Companies are already using AI for customer relationship management, underwriting, detecting fraud or security breaches, automated processes, and even monitoring social media to assess brand perception. Through AI, analysts are given access to data which helps them come up with better suggestions about what the company should be doing. For one, AI takes the mundane, repetitive tasks away from them, so that they can devote their time to valuable collaboration, supporting decision-making, and understanding the needs of customers.

For business analytics, especially, a big benefit of AI is its ability to automatically gather and process far more information than one person (or even a team of people) could do, in as little time. Even when some automation is involved with data gathering and clustering, there is nothing like the power of AI for business analytics generation. This technology is capable of automatically scanning through vast layers of data, uncovering patterns, and creating alerts to try and anticipate or prevent problems, as well as mining for insights and market opportunities, all quickly and automatically. From there, through machine learning and human-machine learning processes, AI starts learning and improving its analyses even more, until it is self-correcting problems which, up until that point, would have mobilised scores of employees within any business.

Artificial Intelligence might look a bit complicated if you look at it from the outside, but it is a technology your business could reap great benefits from. AI works best as a collaborative function throughout an organisation, using reliable data and processes to augment a clearly defined business strategy aligned with an organisations culture and values. It influences the way HR is used, driving changes to business processes and the organisation structure.

Many businesses are already using various types of technologies - cameras, sensors, data-collection software, and others. Large companies are shifting their focus towards developing AI capabilities and changing their business strategies as a result. Companies in various industries are investing in AI and related technologies and are banking on them heavily. AI is a long way off from telling businesses to buy new AI technologies, but it may not be too far away.

We are already seeing the phase of the business in which massive changes driven by technology are helping us solve many problems to reach optimal growth. Understanding the transformation can help innovators, corporate leaders, and practitioners move ahead. As agents of change, analysts should prepare to navigate the changes that will come with the coming technologies, which are human-cantered. As AI matures, the world will witness new start-ups, a myriad of applications in the enterprise and in consumers, as well as displacement of some jobs and creation of whole new ones.

The capacity to capture and process data is rapidly improving, offering new opportunities for the transformation of how businesses work. Large data sets are the raw materials to produce the deep business insights that enable improvements to existing business operations and drive new lines of business. This really does change the nature of a business analysts’ role, and the business analysts’ overall objectives, but it also helps make the data sets available to them far more precise. Training is not intelligence in the sense that computers are cleverer and now understand the meaning of life; it is intelligence in the sense that it enhances their decision-making abilities by making predictions about actions from a larger data set.

Since The Introduction Of Artificial Intelligence How Has Business Analysis Changed

In sum, artificial intelligence requires business analysts to take their valued skills and apply them to a contemporary context and setting provided by rapid technological advances. If properly explored and utilised, AI could become an excellent supporting tool, which allows business analysts to focus on higher value, more impactful tasks throughout an organisation. Artificial intelligence - a loose term referring to any piece of software that performs activities like humans has taken the business world by storm, introducing new and more effective ways to perform data science tasks as a business analyst.

For all the alarmist predictions of artificial intelligence, and the way in which robots will be taking over humans’ jobs in the foreseeable future, nobody can deny AI’s enormous role in business, since it is increasingly showing itself as an enabler rather than a disruptor. AI and high-level machine learning are being applied to intelligent deployments that include robots, smart cars, consumer electronics, and so on. It is difficult to tell how this technology will evolve, but most experts think that these common-sense tasks are becoming easier to handle by computers.

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