The progressive digitization of economic life means that more and more organizations are using tools based on artificial intelligence. According to the report Unlocking the power of AI by the consulting firm Deloitte, over 90 percent of companies want to achieve a higher level of AI maturity within the next 3 years. However, the realization of these plans depends on many factors such as having appropriately qualified employees or the organization’s ability to optimize the implementation process of machine learning solutions.
According to the report’s authors, which is based on discussions with over 600 representatives of leadership positions in companies from different industries, the key factor in the adaptation process of artificial intelligence (AI) solutions are Machine Learning Operations (MLOps). MLOps is a set of practices that enable the optimal implementation of machine learning (ML) in the production process.
The primary goal of MLOps solutions is to implement machine learning in an automated way, allowing for efficient scaling and maximizing effectiveness. Equally important is the issue of consistency and repeatability in the approach to adapting emerging AI solutions, especially considering the pace of AI development. According to the authors of the Deloitte report, companies with advanced MLOps capabilities will be able to maximize the benefits of using the most advanced tools based on AI algorithms. This includes deep learning solutions such as generative models or reinforcement learning, 41 and 42 percent of respondents plan to use these in the next twelve months respectively.
“A significant proportion of the surveyed companies recognize the benefits of using solutions based on artificial intelligence and machine learning. However, a key issue for the ability to adapt new technology is the entity’s past experience in implementing AI and ML. The dynamics of the emergence of new digital tools means that the ability to gain a competitive advantage will increasingly depend on the predisposition to improve processes using modern solutions” – says Michał Sosinka, partner associate, Cybersecurity, Deloitte.
Key Role of Architects
The business value forecasts presented in the report generated by machine learning show how big an impact this technology has on the global economy. According to the authors of the report, by 2025 the business value generated by artificial intelligence and machine learning will amount to $4.4 trillion. MLOps solutions will also be crucial – this market is expected to worth $4 billion within the next two years. It’s no wonder that the vast majority of businesses are interested in this area. Deloitte’s analysis indicates that, 9 out of 10 surveyed entities plan to join the sector or market leaders in AI implementation within the next three years.
The vast ambitions of entrepreneurs, however, face several challenges related to the adaptation of artificial intelligence tools. One of them is the perception of an entity’s maturity in this field by decision-makers in the companies. The survey results show that those in leadership positions seem to be more optimistic about the entity’s progress than staff with high technical qualifications. In the first group, over 50 percent consider their organization mature in this field, and almost one-fourth as very mature. At the same time, the percentage of responses among employees with high technical qualifications was 45 percent and 13 percent, respectively.
The respondents also pointed out a great demand for employees with skills enabling smooth implementation of AI or ML solutions. Currently, companies and organizations are primarily looking for IT architects (28 percent of responses), MLOps solution engineers (26 percent), and cloud service engineers (26 percent).
The authors of the study also highlight an area that is not seen as a key challenge by the majority of respondents in the process of achieving AI maturity. This is the issue of legal regulations, which were mentioned by only one in ten respondents. At the same time, the rapidly changing regulatory environment requires that MLOps solutions are consistent with the applicable legal regulations.
– “The pursuit of full maturity in the field of artificial intelligence is a challenging task. Achieving mastery in this field demands a well-thought-out strategy. Not only should it take into account financial aspects, but also the competences needed throughout the process and key regulatory issues. In the age of digitalization of the global economy, companies aiming to be leaders in their sectors must adopt the latest solutions based on artificial intelligence and machine learning. This is the only way to maintain a dominant position when information is the most valuable market asset” says Piotr Mechliński, partner associate, Risk Analytics & AI, Deloitte.
About the study
Between May and September 2022, Deloitte surveyed 621 key decision-makers regarding artificial intelligence and data analytics in companies from the FMCG, energy, industrial, financial services, life sciences, medical, government administration, public services, media, telecommunications, and technology sectors. The respondents from 7 countries (Australia, Canada, Germany, Japan, South Africa, the United Kingdom, and the United States) were representatives of management (CTO, CIO, CDO), department heads, directors, vice presidents, and technical department workers (e.g. database architects, data engineers, architects, and engineers).
