Beyond the Algorithm: Why AI Success is About People, Not Just Code

Panellists: Jessica Murillo, Vice President and COO, IBM Technology Lifecycle Services, IBM, Ron Bednar, Vice President of Services, North America, Vertiv, Girish Juneja, Chief Digital Officer, Dover, JT Thakkar, Director of Global Services, Carestream

Key Takeaways:

The expert panellists at a recent industry event, including executives from IBM, Vertiv, and Dover,  discuss the reasons why AI success is not only about algorithms but also about people, culture, and organizational preparedness.

• AI implementation success is determined by the preparedness of an organization’s people, processes, and culture
• Employees can be introduced to technology by starting small with AI apps.
• The ROI of AI can begin with soft measures such as employee engagement and time to resolution.
• The success of AI requires cross-departmental cooperation, particularly between IT and service teams.
• Explainability increases trust in AI because employees need to know how artificial intelligence makes its decisions.
• The gap can be closed with the help of Field Service Management (FSM) software that incorporates AI into everyday operations.

The AI Hype vs. Reality

Artificial intelligence (AI) has ceased to be a distant dream and has become a reality and a key component of business strategy. However, the discussion often gets lost in the technology itself, forgetting a critical fact: the success of AI is not determined by the best model or the most advanced algorithm. It is the extent to which an organization is prepared to adopt AI, including the individuals, procedures, and culture that must be in place.

AI models and applications are valuable tools, but they only work when well-integrated into an organization’s workflows. This blog discusses the reasons why the successful implementation of AI is not only about technology, but also about empowering individuals with artificial intelligence and ensuring the organizational foundation is prepared for AI.

Building a Foundation: Purpose and Productivity

The panellists mentioned businesses must establish the role of AI in their operations before implementing a single line of artificial intelligence code. Is the goal to reduce costs? Improve customer experience? Or to empower employees and make them more productive?

Start Small, Think Big

Start with small applications. Provide workers with AI-based applications that can perform basic tasks such as document summarization or data analysis of large volumes of data. You can begin small and enable the workforce to become accustomed to using AI. This will eventually generate a wave of ideas that can support larger projects, such as predictive analytics or AI-based scheduling optimization.

The ROI Conversation

The benefits of AI may not be immediately evident in the form of cost savings. Instead, ROI is frequently observed in KPI improvements, including faster resolution times, fewer internal escalations, and increased employee engagement.. These less challenging KPIs result in a more efficient and profitable service organization.

AI deployment’s meaning goes beyond just technology. It is about enabling businesses with AI and ensuring that all levels of the organization can utilize the tools. This mindset shift is essential for a seamless AI deployment across departments.

Blind Spots: Organizational Hurdles to AI Success

Although AI has enormous potential, there are numerous pitfalls organizations face that derail their efforts. The panellists mentioned that these blind spots should be addressed at the beginning of the AI adoption process.

Siloed Leadership

The implementation of AI cannot be confined to the IT department. AI integration & deployment involve interdepartmental cooperation. The IT and business units should collaborate with the service team to develop solutions that address the organization’s actual needs.

The Data Quality Myth

A common myth is that organizations possess all the data they need. Nevertheless, a more detailed examination typically reveals low data quality. The quality of AI models is limited by the quality of the data on which they are trained. When the data is faulty, the insights obtained will also be incorrect. Before scaling AI initiatives, it is essential to prioritize data management and continuous improvement.

The Fear Factor

Employees are often afraid of AI, especially when they are concerned about job security or when they do not understand what artificial intelligence is. This fear has to be overcome through transparency. Utilize AI as a means to empower, not replace, employees.

Empowered by AI, frontline workers can use these tools to minimize workloads and enhance decision-making. Through trust and transparency, organizations can eliminate the fear factor and foster a more collaborative workplace by leveraging AI.

The Power of the Frontline: A Bottom-Up Approach

The panellists pointed out that the most effective AI strategies are not top-down, but bottom-up.

Employee-Led Innovation

It is essential to engage your frontline teams in the development of AI solutions. Organizations can ensure that the end product is one that employees are willing to use by allowing them to define the problems they face and assisting in creating business cases that address these issues.

Trust With Explainability.

Employees should have confidence in the recommendations of AI. This involves creating systems that can be explained, allowing technicians to understand how AI can empower any business. Supporting AI recommendations with professional analysis at pilot stages will contribute to confidence and adoption.

Measuring What Matters

In addition to conventional KPIs, such as time-to-resolution, companies must also consider new KPIs, including employee engagement, shorter innovation cycles, and data quality. The goal is to develop a framework that demonstrates how AI is enhancing the entire organization, rather than merely addressing individual issues.

The solutions powered by AI make employees feel supported in their day-to-day activities. By empowering employees with AI, organizations can achieve significant improvements and enhance outcomes throughout the organization, including increased customer satisfaction and improved employee retention.

Strategies for Successful AI Adoption

To fully leverage the potential of AI, the panellists recommended that organizations must adopt comprehensive strategies that are both technology-driven and people-centred. The following are some of the most important tips for successful AI implementation and addressing the most frequent obstacles to adoption:

• Begin with Clear Objectives: Clearly define the purpose of AI from the outset. Regardless of whether it is to enhance customer experience, employee productivity, or operational efficiency, clear goals can help keep the organization on track and keep AI initiatives focused.
• Encourage Interdepartmental Cooperation: AI projects should involve more than just the IT department. The combination of service teams, business units, and IT enables the development of solutions that are viable, scalable, and acceptable throughout the organization.
• Invest in Training and Support: To achieve success, AI requires employees to receive appropriate training and support. Empowering employees with artificial intelligence will help organizations ensure that the technology is utilized efficiently and that employees are not intimidated by AI tools.
• Pay attention to Continuous Improvement: AI models are never flawless, and neither is the data that drives them. Periodically evaluate AI results, gather user feedback, and enhance the system. AI models must evolve to meet the changing needs and goals of businesses.
• Make it Transparent and Explainable: To be trusted, AI must be transparent and explainable to employees. Pay attention to the development of systems that can describe the decision-making process of AI, allowing users to be simply comfortable with the recommendations made by artificial intelligence.

A Note on Field Service Management (FSM) Software

The effective use of AI in field service will be maximized when it is combined with FSM software. FSM platforms will provide the framework needed for AI-based service strategies, as they can serve as the central location for data, processes, and personnel.

By supporting a people-centric and bottom-up strategy, FSM solutions can significantly enhance technician performance, provide practical insights to drive ongoing progress, and offer a seamless experience for both employees and customers.

AI model deployment in FSM software can bridge the gap between data and decision-making, enabling organizations to deliver quicker, smarter, and more personalized services. The presence of AI-empowered solutions on these platforms ensures that teams are supported, ultimately improving the customer and employee experience.

Conclusion: A People-Centred AI Journey

The panellists concluded that AI is not about replacing people; it is about empowering them. The deployment of AI is not only about advanced algorithms and data models, but also about establishing a culture where artificial intelligence is perceived as a tool to enhance human abilities.

At Praxedo, we understand that the most effective AI journeys are people-centred. Our FSM platform seamlessly integrates AI into your processes, empowering technicians, supporting employees, and enabling smarter decisions. AI is not a substitute; it is a companion in the changing world of field service management.

FAQs:

1: Why is the success of AI in organizations more than just technology?

The deployment of AI is not only about the best algorithms or data models. The success of AI hinges on having the right people, processes, and culture in place to facilitate it. To deploy AI successfully, it is important to create a favourable atmosphere by training and setting clear goals.

2: How can AI improve employee engagement and productivity?

Simple tasks, such as data analysis or document summarization, can be automated using AI application deployment, allowing employees to focus on more valuable tasks. This leads to better employee experience and engagement. Beginning with smaller AI projects will enable employees to feel more at ease with artificial intelligence and even participate in more advanced projects in the future.

3: What are some common hurdles that hinder AI success in organizations?

Siloed leadership is one of the greatest challenges, where AI is managed by a single department (typically IT). The success of AI will require the cooperation of various departments, including IT, service, and business units. Additionally, organizations must address the fear factor, where employees are concerned about losing their jobs or lack confidence in the technology. This can only be overcome through transparency and communication.

4: How does FSM software support AI deployment in field service organizations?

Field service management software (FSM) is key to the smooth implementation of AI. FSM software provides the framework necessary to integrate AI into field service operations by centralizing data, processes, and workflows. This will ensure that AI-powered tools are utilized efficiently, empowering technicians and enhancing service delivery.