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While organisations acknowledge the potential of AI, there’s a significant gap between organisational adoption and personal use by employees.
The rapid advancement of Artificial Intelligence (AI) is reshaping industries globally, and emerging Europe is no exception.
As a consultant engaged with technological developments in companies, I’ve observed a fascinating trend: while organisations acknowledge the potential of AI, there’s a significant gap between organisational adoption and personal use by employees.
- Inventing the future, rather than retrofitting the past
- CEE’s EU members need innovation for a new growth model
- Emerging Europe is no stranger to transformation
This variance presents both a challenge and an opportunity for companies to explore AI’s full potential.
A recent survey I’ve run involving 107 organisations across various industries from different regions sheds light on this phenomenon. The research combined both quantitative methods—a detailed survey—and qualitative elements through follow-up individual interviews with 20 of the respondents.
This mixed-methods approach allowed for a better understanding of the patterns and perceptions surrounding AI adoption. The study reveals that 86 per cent of organisations have adopted AI in some form, yet there’s a notable lag in official implementation compared to the personal engagement of employees with AI tools.
Employees leading the charge
One of the most striking findings is that 87 per cent of employees in organisations without official AI adoption are personally using AI tools, such as generative AI platforms like ChatGPT. This high level of personal engagement suggests that employees recognise the value of AI for enhancing efficiency and productivity in their daily tasks.
This enthusiasm is a powerful asset. Employees are not just ready but eager to integrate AI into their workflows. They are experimenting with AI-driven solutions to automate routine tasks, gain advanced data insights, and improve decision-making processes. Their proactive approach indicates a bottom-up push towards innovation that organisations can leverage.
A multiple-choice question in the study also reveals that there are multiple originators of AI initiatives. And these initiatives are not solely driven from the top. While 68 per cent of respondents indicated that executive leadership are key originators of AI projects, a significant number of initiatives are also sparked by research and development teams(64 per cent), and data science teams (60 per cent).
Other departments such as the innovation/strategy office (58 per cent), IT department (57 per cent), enabling function managers like HR and marketing (56 per cent), and business unit or operation managers (55 per cent) also play crucial roles in initiating AI projects.
This diversity in originators highlights that AI adoption is often a collaborative effort across various levels and functions within an organisation. It underscores the importance of fostering an environment where ideas can originate from any part of the company, encouraging innovation and facilitating a more holistic integration of AI technologies.
The confidence correlation
The survey also highlights a clear correlation between AI adoption at the organisational level and employees’ confidence in understanding AI technologies.
In organisations where AI is integrated into operations, 71 per cent of employees feel confident in their understanding of AI. In contrast, only 47 per cent feel the same in organisations without AI adoption.
This confidence gap underscores the importance of organisational support in fostering a culture where employees feel equipped to utilise AI effectively. Providing training and resources can empower employees, boosting their confidence and competence in using AI tools.
Challenges hindering organisational adoption
Despite the evident benefits and employee readiness, several challenges are holding back full-scale AI adoption in organisations.
Firstly, resistance to change. Over 52 per cent of organisations cite organisational inertia and skepticism as significant barriers. This resistance often stems from a lack of understanding of AI’s benefits and fears about job displacement.
Then comes a lack of skilled personnel. Some 46 per cent face a shortage of employees with AI expertise. This skills gap hampers the development and implementation of AI initiatives.
Thirdly, data privacy and security concerns. For 41 per cent of organisations, concerns about protecting sensitive data and complying with regulations pose substantial obstacles.
These challenges are particularly pronounced in emerging Europe, where rapid technological advancements can outpace the development of supporting infrastructure and regulatory frameworks.
Exploiting the opportunity
To bridge the AI adoption gap, organisations should consider several strategies.
These include leveraging employee enthusiasm, such as recognising and utilising the proactive efforts of employees who are already engaging with AI tools. Their hands-on experience can drive pilot projects and small-scale implementations that demonstrate AI’s value.
Another is investment in training and development. Organisations can address the skills gap by providing comprehensive training programmes. Upskilling employees not only builds internal expertise but also increases confidence in using AI technologies.
Promoting a culture of innovation is also recommended, through encouraging open dialogue about AI’s potential benefits and challenges. By involving employees in decision-making processes, organisations can reduce resistance to change.
Clear policies/guidelines can also be implemented. Come up with a consideration for ROI of these projects. Also, establish frameworks that address data privacy and ethical considerations. Clear guidelines help mitigate risks and build trust among stakeholders.
Finally, assess departmental differences. The survey suggests variations in AI use across departments and managerial levels. Organisations should evaluate these differences to ensure equitable access to AI tools and resources, maximising overall effectiveness.
Looking ahead
AI’s dynamic progress means that what we know today may evolve by tomorrow morning. Our knowledge might be obsolete before we leverage it further. Organisations that create a foundational mindset and embrace continuous learning will be better positioned to capitalise on AI advancements and extract ROI from the projects.
While most of the interviews revealed massive differences in terms of initiatives, usage and, as expected, allocated resources between large companies and smaller ones, AI as a technology is quite democratic and, with the right attention, any company can benefit from it.
By bridging the gap between employee initiative and organisational support, companies can access new levels of innovation and efficiency. The key lies in empowering employees, fostering a supportive culture, and proactively addressing the challenges that hinder adoption of AI.
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