Artificial intelligence gets a lot of media attention, and for good reason. Surveys of CEOs conducted by organizations like Gartner and EY have predicted it to be the most disruptive technology of 2024. This is because an AI-augmented workforce provides increased efficiency and productivity, enhanced data analysis and decision-making, and automation of routine tasks.
For example, imagine an employee’s timesheet being tracked automatically so they can focus on higher-value tasks.
The Pros and Cons of AI
The impact of AI is clear. It streamlines operations by processing vast amounts of data at speeds incomprehensible to humans, reducing downtime, and optimizing workflows. It also enables predictive maintenance in industries with heavy machinery that can fail and cripple operations. And it provides data-driven insights that were previously hidden or too complex to discern.
Of course, there are also challenges, including employee anxiety over displacement and fear of redundancy. Automation through AI and machine learning can make certain jobs obsolete. And, if they aren’t immediately displaced, employees have concerns about its introduction into the workforce.
The Ethical Dilemmas Surrounding AI
Making matters worse, AI systems are trained on data. Biases in this data can be perpetuated or even amplified if not kept in check. This makes transparency and accountability important as developers work to address moral and ethical concerns.
It’s a topic leaders are just now starting to think about. Strong governance is needed to face these obstacles head-on to ensure human and AI integration run smoothly.
The Impact of AI on the Workforce
Although the recent wave of development with large language models (LLMs) and other generative AI has leaders finally understanding the power of these tools, AI development has been around for some time. American Express, for example, employs AI to analyze millions of transactions in real time. It identifies potentially fraudulent activities, saving the company millions and enhancing customer trust.
The most important aspect leaders need to be aware of in an AI integration is their ethical responsibility. It’s tempting to focus on the bottom line and drive efficiency, but leaders have a responsibility to prioritize human beings with a human-centric approach. This requires soft skills like empathy and understanding to create an inclusive company culture built on trust and acceptance.
Taking Bad Actors Into Account
However, with great power comes great responsibility. These AI systems work with large volumes of proprietary data, and developers aren’t always transparent about updates. Bad actors can warp the data (check out this AI poisoning tool from researchers at the University of Chicago), and data breaches at companies like OpenAI and Microsoft’s Wiz expose the problems that could occur.
Because of this, leadership needs to implement a strong human and AI integration plan accounting for potential hazards while focusing on an AI-augmented workforce.
Fostering Human and AI Integration
It’s important for leadership to set the strategic direction of the human and AI integration. They must have a clear understanding of their strategic goals, whether that’s improving efficiency, enhancing customer experience, or driving innovation.
The AI rollout should align with organizational goals and involve all stakeholders to ensure buy-in. Employee involvement is essential, and this means being transparent and communicating priorities and goals to the entire team. Create a forum and foster a dialog among all applicable stakeholders (internally and externally) to address concerns and clearly define expectations. This puts everyone on the same page.
Here are four key steps to rolling out an AI-augmented workforce:
1. Identify AI Integration Opportunities.
The first step is a comprehensive assessment of your organization’s operations. Leaders must identify areas where AI can add significant value, like enhancing customer service, streamlining data analysis, or optimizing supply chain management.
A gap analysis is crucial in this phase, comparing the current state of operations with the desired outcomes to pinpoint specific gaps that AI can effectively address. Estimating the potential return on investment (ROI) for AI initiatives is equally important in determining the prioritization of AI projects; focus on those that offer the most impact and are feasible within the organization’s capabilities and resources.
2. Build AI Competency.
Success in AI integration is heavily dependent on the workforce’s ability to adapt and work alongside these new technologies. Skill mapping is essential to identify the specific skills and knowledge that employees will need in an AI-enhanced workplace. It’s essential to recognize that training needs will vary. Investing in customized training programs that cater to different roles and skill levels within the organization is vital.
Because AI and related technologies are continually evolving, fostering a culture of continuous learning through regular training sessions and refresher courses is crucial to keep staff up-to-date with the latest developments and applications in AI.
3. Create Synergy Between AI and Human Teams.
Building effective hybrid teams that combine AI systems and human employees is critical. These teams should leverage the strengths of both — AI’s capabilities such as data processing and consistency, and human skills like creativity and empathy. Clearly defining roles within these hybrid teams is imperative, ensuring employees understand when to rely on AI and when to apply human judgment.
It is also essential to invest in collaborative tools that enhance the interaction between AI and human teams. These tools, such as intuitive dashboards, alert systems, and communication platforms, can significantly improve productivity and the overall efficacy of AI integration.
4. Continuously Improve Through Engagement.
It is pivotal to implement an open feedback system where employees can share their experiences and suggestions regarding AI tools. Regular meetings, surveys, or suggestion boxes can serve as effective channels for gathering this feedback, ensuring your AI processes are evolving to meet changing needs and remaining user-friendly.
By actively seeking and responding to employee feedback, leaders improve AI systems and empower their employees, making them active contributors to the AI integration process. This approach enhances the effectiveness of AI tools and fosters a sense of ownership and engagement among the workforce.
AI is a powerful technology that can augment human capabilities in the workforce. However, great care must be taken to ensure its implementation is both ethical and efficient. With a strategic approach, leaders can build an AI-augmented workforce that improves the bottom line and everyone’s quality of life.
Energy Solutions Architect and Senior IT Transformation Leader
Chad Alessi is an experienced leader in the energy industry, driving IT transformation for over 20 years in oil and gas operations, engineering, project management, and operations consulting. He has held various leadership positions throughout his career, including Director of Operations for Williams Energy and Senior Engineer and Supervisor of Operations at Kinder Morgan.