- Introduction
The explosion of data is reshaping management accounting, shifting it from traditional sources of information to a more analytical approach. The use of both structured and unstructured data enhances decision-making and the predictive capabilities of businesses.
The rapid adoption of big data analytics (BDA) within accounting environments confirms this shift. As analytical thinking becomes central to control and planning, the use of BDA to leverage data is becoming increasingly important.
However, this transition is not without cost. Digitalization brings significant opportunities, but at the same time increases the complexity of accounting processes. There may be risks arising from incorrect or too rapid decisions, based on inaccurate forecasts. Other studies highlight that big data may complicate the cost structure.
On the other hand, data analysis can improve decision-making and business planning due to the value of data in accurate and timely information. The digitization of management accounting systems can automate the preparation of financial statements, consolidate reports and reduce human errors, enhancing the quality of information and leading to more effective decisions.
Despite technological advances, excessive interpretations that prejudge the “end of accounting” should be avoided. Real-time accounting information and advances in data analytics may change the nature of the profession, but they do not negate its importance. The accounting dialogue remains core to the business function.
2: The Impact of Digital Technologies on Management Accounting
Digital technologies are transforming the production paradigm, connecting the physical world with its digital equivalent, enabling machine-to-machine communication, enhancing collaboration across the value chain, and empowering intelligence in production processes. These changes are expected to fundamentally impact business models and management accounting.
The integration of new digital technologies into management accounting paves the way for real-time recording of business transactions across the value chain, promoting real-time decision-making. However, further empirical evidence is needed to confirm the practical viability of this approach. Digital technologies are fundamentally reshaping:
- accounting procedures,
- the types of data used and
- decision-making methods.
From enhancing predictive capabilities to providing real-time controls and analytics, digitalization is progressively transforming the practice of management accounting. However, the impacts of digitalization remain conflicting:
- Some researchers predict a radical revolution in the field.
- Others believe these are just mild changes or identify new risks.
These contrasts highlight the multidimensional nature of digital transformation, and demonstrate the need for ongoing empirical research that will clarify the nature and extent of these changes.
3: Artificial Intelligence (TN) in Management Accounting
Artificial intelligence (AI) is having a transformative impact on management accounting, creating both significant opportunities and complex challenges. AI promises to automate repetitive and standardized accounting tasks, increasing the efficiency of the profession. However, the degree of technological complexity and the relative novelty of its integration into the accounting industry raise concerns about its full utilization.
To date, research has focused mainly on expert systems and knowledge-based systems, with limited application of modern techniques, such as machine learning (ML) and natural language processing (NLP). The practical application of AI in management accounting and auditing remains limited.
However, the prevailing view is that AI and ML technologies will bring about radical changes in the profession. The ability to access large data sets makes it possible to identify new concepts and trends that were previously considered undetectable. Given the speed and efficiency of AI compared to the human factor, the role of accountants is being redefined, requiring new skills.
As AI systems evolve, routine tasks for management accountants and auditors may become automated. However, vigilance is needed regarding the risks associated with over-reliance on AI technologies, particularly in decision-making.
Contrary to optimistic predictions, empirical research shows that automation does not necessarily guarantee cost savings, which requires further research to confirm these assumptions. New AI technologies, such as:
- explΤΝnable AI,
- generative AI,
- and large language models (LLMs),
They have a strong transformative potential. They offer faster data analysis and improved decision support. However, their integration into the accounting sector is not yet fully empirically documented, indicating the need for further research.
4: LLMs, ChatGPT, Ethical Issues and Interpretability in AI
The recent proliferation of genetic AI tools and large language models (LLMs) has given management accountants immediate access to unprecedented information processing capabilities. LLMs, with their ability to answer natural language questions, provide increased power to the use of AI in the accounting profession.
The ChatGPT example highlights this transition: it offers immediate benefits such as cost reduction, time savings and human resource free-up, enhancing operational efficiency. However, the nature of LLMs as “black boxes” raises issues of transparency, accuracy and confidentiality. The inability to fully understand the processes underlying their responses, combined with the lack of sufficient information on training data, increases the risk of:
- prejudices,
- inaccurate estimates,
- and violation of ethical principles.
The lack of trust in AI predictions is exacerbated when they are based on questionable data or reveal negative trends. There is a risk that managers will ignore the algorithms’ recommendations, especially when they do not understand how the decisions are made.
The so-called "black box problem" is a critical obstacle to the adoption of ML techniques in management accounting. The solution can come from explainable AI methods, which enhance the interpretability of algorithms, increasing the transparency and understandability of the decisions made by AI.
The use of internal and external data in AI accounting systems requires special attention regarding:
- privacy,
- regulatory compliance (e.g. GDPR),
- risk management,
- and accountability.
There is insufficient focus on the consequences of potential data misuse. The need for transparency and traceability of systems is crucial, both for the acceptance of AI tools and for the ethical operation of businesses.
Increased experience and training in the use of these tools may reduce concerns, but the systematic integration of principles of transparency and ethics remains fundamental.
5: Future Roles of Controllers and Management Accountants in the Age of AI
Artificial intelligence and digital transformation are fundamentally changing the roles of management accountants and auditors, necessitating a new mix of skills and competencies. An emerging field of research focuses on fears of job losses due to AI as automation takes over essential and repetitive tasks.
Despite concerns, this transformation does not necessarily mean a reduction in the importance of accountants; on the contrary, it creates opportunities for a transition to more strategic and analytical roles. Management accountants are being called upon to transform into:
- strategic business partners,
- information model designersAnd
- data analysts focusing on decision-making.
Their role extends to collaboration with data scientists, evaluation of intelligent systems and risk management, while they are called upon to act as a bridge between technology, business strategy and management.
New Skills Required: Accountants of the future should have a hybrid profile skills, combining:
Technical Skills (Hard Skills):
- Data literacy: Ability to understand and interpret data.
- Analytics & ML: Understanding basic principles of machine learning and big data analytics.
- IT & programming: Basic knowledge of tools and automation.
Communication and Administrative Skills (Soft Skills):
- Leadership & presentation: Translating complex analyses into actionable business proposals.
- Interdepartmental cooperation: Coordination with other departments to develop joint solutions.
- Strategic thinking: Broadened understanding of the business environment.
Continuous learning, through corporate training and retraining, emerges as a necessary strategy for maintaining relevance in the profession.
Challenges & Risks: Although technology opens up new career paths, significant obstacles remain:
- Skills degradation (deskilling), if professionals become overly dependent on AI.
- Unemployment risk, especially for low-skilled roles.
- Lack of adequate education, especially in analytics and AI technologies.
Cultivating new skills and integrating technological knowledge into traditional accounting practices are critical to the sustainability of the profession.
6: Data Governance, Trust & AI Adoption in Decision Making
The integration of artificial intelligence into management accounting is accompanied by challenges related to data governance, The information quality and trust in the predictions of AI systems.
Management accountants are required to ensure:
- reliability of data coming from multiple sources,
- appropriate integration of internal and external information,
- and converting this data into economically exploitable information.
Η low data quality may negatively impact decision-making processes, increasing the risk of incorrect business strategies. Therefore, assessing the accuracy and provenance of data is a critical role for modern accountants.
Trust in AI Predictions: Despite technological progress, Trust in predictions generated by AI remains a challengeEspecially when:
- the forecasts concern negative or conflicting trends,
- managers are unable to understand how the algorithm reached a conclusion,
- or when there is low transparency in how the models operate (black-box effect).
The lack of explanation reduces the acceptance of predictions by executives. This undermines the usefulness of AI, even when the data and models are statistically sound.
7. Explainable Artificial Intelligence (AI): The solution to the transparency problem: The lack of interpretability of AI decisions can be addressed through explainable artificial intelligence (Explainable TN) (XTN), which:
- makes predictions understandable to people,
- enhances transparency and accountability,
- and strengthens human-machine collaboration.
The use of XTN tools is particularly appropriate for applications in management accounting and auditing, where clarity and understanding of the underlying models are essential for confidence.
8: Business Value, New Career & Retraining of Management Accountants
The rapid progress of artificial intelligence and the digitalization of accounting processes are leading to significant transformation of the management accounting professionThis change is not only about technical skills, but also extends to strategic abilities, the role in decision-making and the new career paths that are emerging.
Career and Professional Identity Transformation: Accountants are no longer limited to tasks of recording or analyzing past data. Instead, they are transformed into:
- trusted business advisors,
- links between technology, data and management,
- co-creators of business value through data-centric strategies.
The profession is evolving towards a hybrid model, in which AI completes and strengthens the human factor – it does not replace it.
Educational Needs & Skills Development: To meet the demands of the new environment, accountants need to acquire:
Technical Knowledge (Hard Skills):
- AI, ML, Big Data & LLMs
- Data visualization and analysis tools
- Programming (Python, SQL, etc.)
Soft Skills:
- Contact & presentation
- Critical thinking & strategic insight
- Collaboration in interdisciplinary environments
Η lifelong learning is now a basic requirement. Organizations must invest in:
- Internal training programs
- Online seminars
- Certifications in modern technologies and analytical tools
Business Value & New Roles: The new capabilities brought by technology enable management accountants to offer:
- Added value in decisions through real-time analytics
- Better adaptation to new strategies digitization
- Participation in the design of new business models
At the same time, new roles are making their appearance, such as:
- AI-enhanced controller
• Data-driven performance analyzer
• Business Intelligence Manager
• Cross-sector data translator
9: Conclusions – The Dynamic and Evolving Relationship of Management Accounting with Artificial Intelligence
The interaction between management accounting and artificial intelligence (AI) technologies is dynamic, evolving and multi-layered. Developments in AI techniques, such as large language models (LLMs), machine learning (ML), deep learning (DL) and explainable AI (XTN), highlight new possibilities and challenges for the industry.
Exkaisies:
- Automate repetitive tasks, with significant cost and time savings.
- Strengthening decision-making with more accurate and real-time data.
- Emergence of new professional roles of a strategic and technological nature.
Challenges:
- Risk of deskilling and dependence on black-box algorithms.
- Lack of transparency and trust in predictions generated by AI.
- Insufficient training for the new demands of the profession.
The Transition Strategy: Sustainable adoption of AI in management accounting requires:
- Investing in continuous professional development.
- Cultivating hybrid skills that combine expertise, analytical thinking and communication.
- Development of data governance frameworks, transparency and ethical use of technology.
Final Thought: The future of the profession does not dictate the disappearance of management accountants, but the redefining their roleRather than being replaced by technology, accountants are called upon to understand, integrate and use it. as a strategic advantageThose who choose to actively adapt will find themselves at the center of operational decision-making, taking on roles with real impact on the value of the organization.
Written by Atsalakis Giorgos, Economist, Associate Professor – and Atsalaki Ioanna, Lecturer, Technical University of Crete, Scientific Data Laboratory
photo by TheDigitalArtist, https://pixabay.com
