Making the Most of AI and New Technologies in Your Organisation through Automation, Governance, and Talent Development
As the influence of artificial intelligence (AI) continues to grow across industries, organisations are increasingly recognising the importance of integrating AI into their operations. From automation tools to AI-driven decision-making and content creation, the possibilities seem endless.
However, for organisations to truly benefit from AI, they need more than just technology; they need the right strategy, governance frameworks, and employee training programs in place.
We’ll take a look at the challenges and opportunities that organisations face when adopting new technologies, focusing on automation, data management, cloud services, and the evolving needs of talent development.
We will draw insights from a recent strategy meeting that delved deep into these topics, outlining best practices and key considerations for leveraging AI effectively in the workplace.
AI in Automation: Moving Beyond the Buzzword
The conversation around AI often begins with automation, which can range from automating repetitive tasks to deploying AI systems capable of complex decision-making. However, the term "AI" is frequently used in budget proposals for tools that simply automate tasks, leading to questions about what qualifies as true AI.
Defining AI in Automation
While many tools automate processes, true AI adds value through machine learning, predictive analytics, and the ability to adapt over time. In a recent meeting, a senior leader raised the question of whether it’s appropriate to label budget requests for automation tools as "AI."
The consensus was that, if these tools automate human tasks with some level of intelligence or prediction, then calling them AI is reasonable. However, the team cautioned against misleading stakeholders by overstating the capabilities of such tools.
Developing an AI Strategy through Planning, Before Implementation
When organisations decide to adopt AI, developing a comprehensive AI strategy is critical before investing in specific tools. Numerous industry leaders advocate the importance of aligning AI initiatives with broader business objectives.
Key Elements of a Successful AI Strategy
Before selecting any AI tool, it's essential to determine the problem you're trying to solve or the process you want to enhance. For instance, some companies are integrating AI to provide conversational interfaces for recruitment data, using tools like Qlik and Amazon’s embedding models. However, it’s crucial to establish the desired outcome before choosing a product - organisations need to understand the outcomes they are aiming to achieve.
Involve Leadership and Allocate Resources: Any AI strategy must involve the organisation’s leadership. Some people at our recent roundtable suggested that the board should have a clear role in steering AI projects. This includes providing resources and overseeing governance, ensuring that AI is implemented in a way that aligns with the company’s vision.
Training and Implementation: The full benefits of AI can only be realised when employees are trained to use these tools effectively. Proper training, particularly when integrating AI into decision-making processes is crucial.
Unified Data Management: The Backbone of AI Success
AI thrives on data, and without proper data management, AI implementations are doomed to fail. During the meeting, the participants stressed the need for a unified approach to managing data across different products and systems.
Data Governance and Permissions
A key challenge that emerged was the difficulty of managing permissions and governance over data. In industries such as pharmaceuticals, obtaining the necessary permissions to use data for AI applications is particularly critical. Organisations need to ensure that their data governance frameworks are robust enough to handle AI-driven tools that require large datasets. Poor governance can lead to legal complications, security risks, and unreliable AI outputs.
AI tools that streamline data management can significantly reduce the time spent on manual data processes. One company shared an example of using AI to manage product information documents, automating the process of updating records across various systems. However, the participants emphasised that a solid governance framework must underpin any data management system.
Managing Cloud Services and Software Tools in the AI Age
With the rise of cloud services, many employees are adopting tools without company approval, a trend known as “shadow IT.” Employees sign up for cloud services like AWS, Google Cloud, and Alibaba using personal email addresses and credit cards, making it difficult for IT departments to manage and secure these services.
Embracing and Managing Shadow IT
The meeting highlighted the challenge of managing these unauthorised tools. However, instead of trying to stamp out shadow IT, the participants agreed that organisations should embrace it while developing better management strategies. This includes establishing clear guidelines for employees about what tools they can use and ensuring that cloud services meet the company’s security requirements.
Recent participants at our roundtable suggested creating a concise strategy document to present to the board, outlining the risks and benefits of cloud services and the steps being taken to manage them. In an age of rapid technological change, lengthy documents often fail to maintain stakeholders' interest, so a concise, well-structured approach is essential.
Training for AI: Preparing Employees for the Future
As AI becomes more integrated into everyday operations, organisations must ensure their employees are adequately trained to use these new tools. One of the most significant challenges highlighted in the meeting was how to train employees for AI implementation, particularly when it comes to coding and cybersecurity.
AI and Coding Skills
Several participants discussed the impact of AI on coding, with one company transitioning from using ChatGPT to Microsoft's Copilot for competitive strategy and data creation. While AI can significantly speed up coding processes, there are concerns that it might eventually lead to a decline in the number of skilled coders. If organisations rely too heavily on AI for coding, there’s a risk that human coders will lose the ability to troubleshoot and solve complex coding problems.
One way to address this concern is to ensure that employees are trained to work alongside AI, rather than becoming reliant on it. Regular training sessions can help employees stay up-to-date on new AI tools while maintaining their core coding skills.
AI's Impact on Content Creation and Problem-Solving
AI is also having a profound impact on content creation and problem-solving. From generating reports to automating marketing campaigns, AI can drastically reduce the time spent on creative tasks. However, this raises concerns about the future of human creativity and problem-solving in a world where AI can produce content at scale.
Balancing AI and Human Creativity
While AI can create content quickly, it lacks the emotional intelligence and creativity that humans bring to the table. Therefore, organisations need to strike a balance between using AI for efficiency and fostering human creativity. In the long term, the key will be to ensure that AI is seen as a tool to enhance human capabilities, rather than replace them.
One participant in the meeting raised concerns about AI’s accuracy when generating code, suggesting that organisations should be cautious when implementing AI-driven content creation tools. Mistakes in AI-generated content can lead to significant problems down the line, so it's essential to have robust review processes in place.
Evolving Talent Needs in the Age of AI
AI is changing the landscape of talent development. As AI automates more tasks, organisations will need to reskill and upskill their workforce to focus on higher-level, creative, and strategic work. During the meeting, participants discussed the need for continuous learning and the importance of retaining talent that is well-versed in AI technologies.
Building a Culture of Continuous Learning
One key takeaway from the discussion was the importance of building a culture of continuous learning. Organisations that encourage employees to learn new AI tools and adapt to changing technologies will be better positioned to succeed in the long term. This includes offering regular training sessions and ensuring that employees are aware of the latest AI developments.
Talent retention was another major concern. AI-driven companies need to invest in their employees, offering opportunities for growth and development to keep them engaged. This is especially important in competitive industries where skilled talent is in high demand.
AI has the potential to transform organisations, but it must be implemented thoughtfully and strategically. As we’ve seen from the meeting, key considerations include developing a robust AI strategy, ensuring proper data management, training employees, and striking a balance between human creativity and AI automation.
Organisations can make the most of new technologies by focusing on these areas while avoiding common pitfalls.
The journey towards full AI integration is ongoing, and while the potential is enormous, so too are the challenges. As AI continues to evolve, organisations must remain flexible, cautious, and forward-thinking, ensuring that they are ready to adapt to whatever comes next.