Many modern technologies can be characterized as disruptive technologies, with artificial intelligence being among those that have a significant impact on the manner of business operations. However, if we delve deeper into this topic, it is vital to understand that, like everything in this world, the use of AI has its advantages and disadvantages. Also, an issue undergoing consideration in business currently is artificial intelligence and the computerization that it is set to bring. Artificial intelligence is changing daily life and business from the smallest elements to the most significant ones, from social media filters and fraud detection to wearable health sensors and tailored shopping recommendations.

The Oxford Training Centre arranged the Future of Work with AI course to provide learners with adequate information on the use of AI in the workplace. It discussed the following approaches to improving organizational performance: workforce planning, digital transformation, workplace automation, and the principles of AI ethics.

What is AI?

The term artificial intelligence describes the programming that underpins the majority of the “smart” devices that people use on a daily basis. The foundation of standard computer programs is a collection of rules, filters, and exceptions that give them the appearance of intelligence. However, none of these programs are based on actual intelligence; instead, they are all following the rules.

Artificial intelligence, on the other hand, deals with a means of enabling computer systems to go through large volumes of data and be capable of changing their behavior depending on previous experiences.

How does AI work?

It is important to note that, at the heart of artificial intelligence is the algorithm, which should be regarded as a set of instructions that are meant to guide a computer. One of the differences between artificial intelligence algorithms and other computing activities, such as in an Excel spreadsheet, is the capacity to change the code. By sending exceptions to its predictions through a feedback loop, an artificial intelligence program can learn and improve its predicted accuracy rather than repetitively performing the same calculations. Furthermore, the majority of the time, artificial intelligence is used on data sets that are significantly bigger than spreadsheets, which can only accommodate a little over a million rows of data.

Artificial intelligence has wide-ranging effects. You may recognize the terms “neural networks” and “deep learning” are sets of algorithms that are based on the structures of neurons in the human brain. Thus, data scientists generate in code artificial neurons that act like the roughly 100 billion neuronal “switches” in the human brain. This allows them to create visual recognition systems that replicate how humans use their sense of vision to navigate the world of objects.

Impact of AI on business

The concept of artificial intelligence is not merely theoretical. Additionally, it is a very useful method of data management that relieves human workers of the weight of automated activities. Here are three ways that a team might use artificial intelligence to increase productivity and success in less time by having machines do some of the work.

1. KPI tracking and visualization

Currently, when business choices need to be made, human workers can access a database of data and do a variety of calculations to assist them in deciding, for example, how to best optimize shipping or when to launch a product. The ability of humans to acquire the appropriate data and pose the appropriate questions is crucial to a large portion of this job. The first way artificial intelligence will assist is by transforming massive volumes of data into visual representations that all team members can comprehend. Artificial intelligence systems can then keep an eye on important KPIs and notify managers when they are in danger from factors that could fool even the most astute businessperson.

2. Deeper insights into consumer behavior

The biggest retailers have been collecting a ton of information about their customers since the beginning of e-commerce, including what they buy, when they buy it, and what they look at before clicking “purchase.” Before artificial intelligence, people handled the task of creating sales leads on their own, using simple methods. Over-intervention and customer attrition are major hazards with this approach. However, customer attrition can be decreased, and customer assistance can be provided at the best moments due to ‌insights generated by artificial intelligence.

3. Maximize human labor

Reducing worker hours spent on report creation and basic decision-making is arguably the most significant consequence of artificial intelligence. A data scientist, who develops, oversees, and operates the processes that allow other human workers to concentrate on higher-level tasks, gains a job for every job lost by someone who used to churn data mindlessly to produce reports, despite the frightening implications of possible job loss.

Applications of AI in business 

By improving operational efficiency and automating repetitive operations, artificial intelligence (AI) is transforming the business sector. 

• Workflow automation and customer relationship management (CRM) are two of the most popular uses. Robotic process automation (RPA) from UiPath and Salesforce Einstein are two examples of AI-powered solutions that manage client contacts, expedite sales processes, and take care of tedious administrative duties. Businesses can expand their operations without incurring correspondingly higher costs due to this automation, which also decreases errors and expedites reaction times.
• AI greatly increases productivity through information management and content generation in addition to automation. Microsoft Copilot and ChatGPT for Enterprise assist the staff members in report writing, distilling, communication, and writing papers with minimal time to find information. The nomadic work environment means that employees do not spend their time in the throes of completing repetitive work; instead, they devote time towards the development of concepts that can be useful to the organization.
• AI is also beneficial in the important application of predictive analysis. AI allows organizations to predict and plan their operations, optimize their supply chain, and manage their inventory as well as marketing strategies based on customers’ preferences.
• It is also altering the creative and marketing industries. Businesses can create customized ads and branding materials at scale with tools like DALL·E Business Suite, which automate the generation of visual content. By providing audiences with visually appealing and pertinent content, this capacity aids firms in improving consumer engagement.
• Additionally, AI agents are being used more and more in departments to handle repetitive jobs and intricate procedures. These intelligent agents free up human workers to concentrate on important projects and innovation by coordinating tasks, keeping an eye on performance, and even interacting with customers. 

Edge AI improves this by offering quicker insights with better privacy and lower bandwidth costs by processing data locally on devices rather than exclusively using cloud computing.

Future challenges for AI in business

Several important obstacles stand in the way of AI’s full potential and broad adoption as it continues to change the corporate landscape in 2025 and beyond.

1. Skill gap and talent shortage

The lack of qualified AI specialists worldwide is one of the most urgent problems. AI project implementation and optimization are hampered by businesses’ inability to locate specialists in data science, machine learning, and AI system management. Although a lot of businesses are spending money on upskilling current staff members and collaborating with academic institutions to create talent pipelines, the gap still exists.

2. Data security

One major concern that arises from the need for handling big data sets used in implementing such systems is security, privacy, and other legal questions. It is therefore important to consider cross-disciplinary solutions to maintain customer data ‘inelasticity’ while at the same time ensuring that AI applications do not breach the GDPR. Of critical importance to avoid falling foul of the law, companies have to maintain a balance between creativity and control over their data assets.

3. Governance and ethical concerns

It is imperative to ensure that the implementation of ethical AI governance involves various stakeholders to minimize abuse and address the subjectivity related to its applications. Uncertainty in regulations and disparate international standards make this problem more difficult.

4. Energy use and its effect on the environment

Because advanced AI models demand a lot of processing power, energy consumption, and environmental issues are increasing. To reduce AI’s carbon footprint while preserving performance, companies and researchers are looking into edge AI, more effective algorithms, and renewable energy sources.