AI will boost quality and efficiency (at the same time!)

The authors of this article, Filip Tichý (Partner at Grant Thornton Slovakia) and Jakub Chudík (Co-Founder at Assetario), take you through the world of artificial intelligence in the AI Breakfast series. This article was written without the use of AI.

We are often asked how artificial intelligence (AI) will affect my audit profession, or more broadly consulting services. It is, of course, a topic that we deal with intensively and that is fascinating to us, as it is about our profession and about our business. But this article will not be about the future of audit (maybe next time), but about how AI will break down existing barriers and limitations in various industries.

Most companies and business models naturally has internal conflicting or contradictory drivers, that are difficult to boost or maximize at the same time. For example, in the case of auditing (as well as other service industries), two drivers are significant - quality and efficiency. Some companies are building a top quality, others try to be more efficient. In a year when a company works intensively on improving the quality of services, efficiency may drop slightly and vice versa. Every company is searching for the right balance and its strategic competitive position within its market. And the most successful are companies that can provide high-quality services very efficiently. Therefore, it is not surprising that in our field of auditing, the development of AI is currently taking place in these two principal directions - the involvement of AI to increase quality and increase efficiency. At the same time.

• Increase quality through comparison with endless examples of high-quality audit files, methodology and standards and other benchmarks, automatic search for errors, inaccuracies or missing documentation.
• Increasing the efficiency of the audit, on the other hand, AI will strengthen through the gradual automation of the execution of audit procedures. Automation is gradual, in the first phase (which is already underway) incremental and partial small improvements in "copilot style", in the second phase scaling and in the third full automation? We will see.

The best part is that AI does not have to make any compromises between quality and efficiency. Attributes that are in natural conflict for humans do not have such barriers at all from the AI point of view.

In various industries and business models, AI has the potential to solve conflicting factors where humans usually have to make compromises. Here are some examples (to increase the efficiency of writing of this article, pre-prepared by Copilot with subsequent qualitative editing by Filip and Jakub). It is interesting to observe that in these examples quality vs. efficiency is a recurring case, but also personalization vs. standardization or maximization vs. sustainability.

• Healthcare: In healthcare, there is often a trade-off between personalized care for the individual patient and the efficiency of treating as many patients as possible. Artificial intelligence can analyze patient data and provide personalized treatment plans, while streamlining administrative tasks to improve overall efficiency.
• Retail: Retailers often face a conflict between customer customization and operational efficiency. Artificial intelligence can help by analyzing purchasing patterns and providing personalized recommendations, while optimizing inventory management and supply chain logistics.
• Manufacturing: The manufacturing sector struggles with the balance between product customization and production efficiency. Artificial intelligence can enable mass customization through advanced algorithms that adapt production lines in real time without sacrificing efficiency.
• Financial sector: In finance, the trade-off between risk management and customer service can be mitigated by AI. It can assess risk using large data sets more accurately than humans, while providing personalized financial advice to customers.
• Transport: The transport industry must find a balance between route optimization in terms of speed and cost efficiency. Artificial intelligence can optimize routes in real time, taking into account various factors such as traffic, weather and fuel consumption, to achieve both speed and cost savings.
• Energy: In the energy sector, it is necessary to find a balance between energy production and environmental sustainability. Artificial intelligence can predict energy demand and adjust production accordingly, while also identifying ways to increase energy efficiency and reduce emissions.
• Agriculture: Farmers often have to choose between maximizing crop yield and sustainable farming practices. Artificial intelligence can analyze soil, weather and crop data to optimize planting, harvesting, irrigation, fertilization for optimal yield and sustainability at the same time.
• Education: Educators are challenged to provide personalized learning while managing large classes. Artificial intelligence can offer students personalized learning paths while helping teachers monitor progress and identify areas that need attention.
• Real Estate: Balancing the risks of investing in real estate with returns is a challenge in real estate. Artificial intelligence can predict market trends and property values, helping investors make informed decisions without sacrificing potential returns for safety.
• Telecommunications: Telecommunications companies strive to provide high-quality services while minimizing infrastructure costs. Artificial intelligence can optimize network performance and predict maintenance needs to ensure quality without overspending.
• E-commerce: The goal of e-commerce platforms is to provide personalized shopping while efficiently managing logistics. Artificial intelligence can tailor product recommendations to individual users and optimize logistics for on-time delivery.

Regardless of the industry, transformational changes facilitated by quality data collection, long-term AI strategy and active use of data-based decision-making await us. It is therefore essential for every manager to think about how he can see these changes as opportunities and use them to become a leader in his sector.