Artificial intelligence can give companies a significant competitive advantage. Goldman Sachs estimates that generative AI has the potential to raise the global GDP by 7%, the equivalent of $7 trillion, over the next 10 years. But the technology also promises to be a critical determinant of business success or failure within the next five to 10 years. It all hinges on effective implementation of AI — currently, 80% of new AI initiatives fail.

While business challenges such as budget constraints and data infrastructure are well-documented, the human aspect often gets overlooked. Frequently, leadership is too quick to adopt the latest innovations, driven by a fear of being outpaced. This mindset leads to hasty investments in trendy solutions without considering how AI tools will integrate into employees' daily workflows, or scale to address broader business opportunities.

Consequently, many organizations deploy AI systems without fostering trust or buy-in among their teams. They fail to take the employee’s view of “What’s in in for me?” These missteps indicate the need for a new model in AI software selection and implementation: a human-centric approach.

In global organizations, complexities abound: Employees juggle multiple roles, workloads are heavy, and there is an expectation to navigate increasing challenges with fewer resources. Such an environment leaves little room for learning new skills or adapting to new platforms, stifling innovation before it can take root. This urgency can create pressure for both management and users.

AI has the potential to deliver unprecedented efficiency gains. According to McKinsey, AI-driven initiatives in marketing, sales and supply chain management have resulted in revenue increases exceeding 5% for many companies. In today's competitive landscape, such gains can be the difference between success and failure. However, fear-based decision-making often leads to implementation failures that contribute to that overall 80% failure rate. Leaders must ask themselves: "Are we truly maximizing our investment in a platform if it misaligns with our intended purpose, or if our team struggles to see its relevance?” We can address this issue by focusing on two essential strategies: vetting and rollout.

Vetting: It involves more than simply selecting the most popular platform. It requires assessing how well the tool automates or accelerates existing workflows, enables new data insights, and addresses specific challenges faced by teams. To achieve this, follow these key steps:

• Identify the particular problems the platform aims to solve, and how it can reshape the potential of your teams to make a bigger impact than perhaps mere transactional execution.
• Consult with management, department heads, individual contributors and partner managers about necessary improvements and new opportunities across the organization. Keep in mind that AI is about more than doing the same thing faster. The technology can also open the door to new insights and opportunities.
• Gather feedback on improvement areas, and compile a list of pain points from various departments and levels.
• Refine your understanding of stakeholder needs by clearly defining the pain points as well as the benefits for your key stakeholders.

The more precisely you define these pain points, the better equipped you'll be to evaluate potential solutions. A comprehensive approach engages key stakeholders early, and will guide you in selecting an AI system that addresses specific challenges and aligns with your overall goals. 

Rollout: User engagement should begin much earlier, during the objective-setting phase. This approach allows key users to engage early and become ambassadors for the future deployment of AI, avoiding the "not invented here" paradigm. By involving key subject-matter experts from the start, you ensure that the AI tool is configured to run your business or supply chain in real-world conditions, not just in theory.

Often, leaders stop at department heads when implementing new systems, assuming they will effectively manage their team’s adoption. Employees may feel imposed upon if they perceive new systems as distractions from trusted methods they already use.

To foster buy-in after selecting the right technology, it's crucial to demonstrate how it will enhance work experience through war room exercises or simple simulations of problem-solving, both before and after. Highlight functionalities that align with initial feedback, and appoint super users within each team to showcase time savings on repetitive tasks. Compare and document the before and after business processes, outcomes and time to value.

Remember that AI is not a magical box. Users need to understand, to an extent, what this "box" does in order to trust its outputs. Such understanding is key to freeing up resources for higher-value work. For example, before implementing AI, three analysts might spend two days a week gathering data from multiple sources to feed into a spreadsheet, only to find that the data was already outdated and no longer reflected current market conditions. With an AI-driven system, each analyst can “recapture” those two days for higher-impact activities, while working with real-time data that reflects current business and market conditions.

This strategy places employees at the center of transformation initiatives, increases the likelihood of successful adoption, and ensures that AI is configured to create an environment that is sustainable and beneficial in real-world situations.

By collaborating with employees from platform selection through implementation, businesses can be among the 20% that fully realize AI's capabilities. A unified effort of "one team, one dream" is essential for navigating this transformative landscape successfully. When done right, it drives both short-term wins and long-term value, creating a ripple effect of innovation and efficiency throughout the organization.

The journey may be complex, but the rewards — in the form of enhanced productivity, improved decision-making, and a more engaged workforce — are well worth the effort. Embrace the challenge, involve your team, and prepare to realize the full potential of AI in your business.

Mark Talens is executive vice president and chief strategy and solutions officer with ParkourSC.