Artificial Intelligence (AI) is revolutionising how organisations operate by enabling machines to perform human-like cognitive tasks such as problem-solving, decision-making, and innovation. Despite its potential, AI remains in its infancy within most large enterprises and is nearly absent in smaller ones, save for some tech startups. Recent surveys indicate that fewer than half of large organisations have meaningful AI initiatives, with many projects still in the pilot or proof-of-concept phase. This early stage of adoption means many organisations have yet to realise significant economic returns from their AI investments.
Applications of AI in Organisations
AI is being leveraged for various objectives, including enhancing process efficiency, improving existing products and services, creating new ones, and improving decision-making processes. Despite media focus on AI reducing headcount, this objective is the least mentioned among organisations.
Initially, AI technologies were used to automate linear, repetitive processes. However, the trend is shifting towards more complex tasks such as decision-making, problem-solving, and creativity, which were previously thought to be beyond the scope of automation. For example, in manufacturing, AI enables humans and robots to work together, adapting to fluctuating demands without the need for manual process overhauls.
Challenges in AI Deployment
A significant hurdle in AI adoption is the difficulty in moving beyond experimental stages to full-scale deployment. Deployment requires integrating AI with existing technology architectures, changing business processes and organisational culture, reskilling employees, and substantial data engineering. Surveys suggest that while many firms are investing in AI, only a small fraction have successfully deployed these technologies at scale. Effective deployment necessitates careful planning from the outset, with some companies adopting structured processes to transition from prototypes to production.
Talent and Skills
The scarcity of AI talent is another critical challenge, particularly for non-tech organisations. Data scientists and AI engineers are in high demand, and firms that cannot offer competitive salaries or are located outside tech hubs struggle to attract the necessary talent. Moreover, there is a lack of consensus on the qualifications required for AI-related roles, complicating hiring and training efforts. Organisations need to focus on retraining existing employees, working with universities to develop relevant programs, and nurturing internal AI communities to build and sustain AI capabilities.
Social and Ethical Implications
The deployment of AI brings several social and ethical concerns, including algorithmic bias, lack of transparency, accountability issues, and privacy invasions. Algorithmic bias can disadvantage certain groups, leading to unfair outcomes in areas such as job recruitment and judicial sentencing. Unexplainable decision outcomes from complex AI models can erode trust and accountability, while privacy concerns arise from the extensive data AI systems require. Addressing these issues involves performing thorough evaluations of training datasets, maintaining transparency, and involving human oversight in decision-making processes.
Future Opportunities
Despite the challenges, AI presents numerous opportunities for transforming work and organisational structures. AI can automate mundane tasks, allowing knowledge workers to focus on more complex, value-added activities. It can also augment professionals by supporting their decision-making processes, although this requires overcoming new coordination challenges and adapting to changes in authority and valuation schemes within organisations.
Leading companies are developing management and governance mechanisms to oversee AI projects, including appointing AI champions, creating AI centres of excellence, and formulating comprehensive AI strategies. The democratization of AI through user-friendly tools enables a broader range of employees to engage in AI projects, further driving innovation.
While AI is still maturing, its impact on organisations and society is profound. Companies need to develop strategies for effective AI deployment, address talent shortages, and navigate social and ethical implications to harness AI’s full potential and transform their operations and workforce for the future.
See
Artificial Intelligence in Organizations: Current State and Future Opportunities
MIS Quarterly Executive: Vol. 19: Iss. 4 , Article 4, 2020
Hind Benbya
Deakin University
Thomas H. Davenport
Babson College
Stella Pachidi