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Preparing your Business for Generative AI: 3 Crucial Strategies for Seamless Integration

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Despite first appearing a short time ago, Generative Artificial Intelligence (AI) is already transforming the way we work. AI tools are now regularly deployed across a wide range of industries to perform a variety of crucial tasks such as: managing inventory, monitoring cybersecurity, streamlining customer service, facilitating IT operations, and generating marketing content. While the use of Generative AI is becoming increasingly common in business, the path to a successful digital adoption remains far more elusive. In fact, only 54% of AI projects make it from pilot to completion. When an AI initiative fails, there is a measurable loss of time, money, and effort. Planning makes the difference between a successful adoption and the many failed projects mentioned above. By aligning your purpose, strategy, and stakeholders, creating a plan to drive engagement, and assessing your organization’s risks, you can help ensure  AI adoption success.

Align Your Team on Purpose, Strategy, Governance, and Roles & Responsibilities

When launching an enterprise-level AI initiative, your first step is to build a consensus on what you hope to accomplish. Begin by assembling the project’s key stakeholders, including the members of your AI advocacy team. The actual members will vary between organizations, but should include members of the project team, your chief data officer, data leaders, and, if you have them, any chief AI officers. You will also want to include members of the IT and risk management teams, as well as any relevant business stakeholders.

Once you have assembled your team, it’s time to focus on the project itself. Create a document outlining the project’s purpose, objectives, and goals. The idea here is to ensure that everyone agrees on what your project is trying to accomplish. Identify the specific parameters and key performance indicators (KPIs) for your program. Doing this will provide a unified vision of the project’s expected outcomes and benefits.

Once the purpose, goals, and KPIs have been defined, it’s time to create a governance structure. This framework will lay out key rules and procedures necessary to keep the project on track and achieve the goals that you’ve identified. Be very clear on the key stakeholders’ roles and responsibilities, so that every member of the team understands what is required of them. This structure should include direct leaders, sponsorship roles, risk management team members, and IT professionals who will manage the technical details related to digital adoption platforms.

Audience Focus: Plan for Engagement, Learning and Performance Support

This stage prioritizes people. To successfully reach their audience, stakeholders must determine the answers to three key questions:

  • How will we ensure users are motivated to use the AI solution?
  • What do users need to know to use the new technology both effectively and correctly?
  • What resources are needed to support users and drive AI adoption?

The first question will help you determine how to motivate users, which will form the basis of your  user engagement strategy.

The answers to the second question will be used to identify an employee training strategy. For AI solutions, the best approach will likely be establishing a set of rules or principles that must be followed, rather than a traditional program that emphasizes steps users need to follow or particular actions  they need to repeat.

The final question will help define the scope of your performance support. This is the content users will reference when using the AI solution on the job. Since AI changes so quickly, it’s crucial to have performance resources that can be easily updated to keep pace as AI technology evolves.

Building Effective Employee Engagement

All change initiatives face resistance, but AI requires a complete change of mindset. Keep in mind that workers will have remarkably different comfort levels when it comes to AI. To properly engage your audience, your team must address this full range of perceptions. That means soliciting their feedback early on. Clear, open communication is critical here. Before your project is piloted, let employees know what is happening and what they can expect. Talk to employees in a variety of roles across the entire organization to gauge their reactions and take note of any pain points they might have. Adoption engagement rates increase significantly when employees see the clear benefit of a change. Determine how AI can make employees’ lives easier and motivate them with messaging that answers, “What’s in it for me?”

Leveraging use cases is another effective way to offset fear and break down employee resistance. Lay out exactly how your organization will be using AI and, just as importantly, how you will not be using it. Clarifying AI’s role in your plan will help remove the unknown and allow employees to react to facts instead of unfounded fears.

Enlist your AI advocates to help drive engagement. Advocates function as the cheerleaders for technology adoption, creating excitement about the benefits AI provides. When creating messaging, brainstorm additional formats that go beyond emails and webinars. Providing work or discussion groups can generate enormous buy-in for your project by enabling employees to work through resistance together and build a team consensus around the use of artificial intelligence.

Provide Employees with the Right Level of Learning and Support

Motivating employees to engage with AI is critical, but if you fail to provide them with the skills and performance support needed to use it properly, your efforts will be wasted. The conversations you have with employees early on will yield valuable insights into the type of training individuals require. Provide mechanisms for support and communicate them to all employees early on. By the time your AI initiative rolls out, users should have a clear understanding of where to direct questions, provide feedback, and request help. Remember, change is far less frightening when employees feel adequately supported throughout the implementation process.

Assessing Project Risk and Readiness: Early Identification is Key

Any platform adoption initiative faces risk, but the work you do early on will determine how effectively the organization can mitigate these obstacles. The risk management, project management, and change management teams all play a critical role in overcoming resistance. Before moving forward with the program, task your team with running a readiness assessment. This will help gauge employee reaction, identify potential obstacles, and prepare your organization for digital adoption. Culture plays an enormous role in how employees react to change. An assessment may point to problems in the corporate culture that must be addressed before a change initiative can take place.

Your project management and change management teams can also help uncover potential risks and offer unique solutions to overcome them. With technology projects, the project management team typically focuses on getting the technology ready for the organization, while the change management team’s goal is getting your organization ready for the system. The result is two teams looking at the same project from two vastly different perspectives. Because of this, members of the change and project management teams can often uncover obstacles that are not apparent to other members of the organization. Ensure that both teams are a part of the initiative from the beginning and put clear, regular communication channels into place between them that last for the project’s entire lifecycle.

Identify Deliverables That Mitigate Risks

Once a readiness assessment has been completed and the risks have been identified, it’s time to develop your solutions. Analyze the risks and brainstorm deliverables that will help mitigate those obstacles. During this phase, it’s important to provide high-level and detailed reporting on both the risks and deliverables and share this with everyone involved in the AI initiative. Providing visibility on the risks and deliverables can help create organizational alignment and ensure that all key stakeholders are clear on the role they play in overcoming obstacles.

Preparing Your Organization for Generative AI

Generative AI offers exciting possibilities for streamlining work and boosting organizational efficiency.

While AI tools do a fantastic job of simplifying day-to-day tasks, the process of introducing AI to your workforce can be remarkably complex. Unlike traditional technology initiatives, AI requires a significant change in mindset to overcome workers’ fears of becoming obsolete. To help ensure a successful adoption, be sure to align your purpose, strategy, and stakeholders, create a plan to drive engagement, and assess your organization’s risks early on. A well-built plan will help create the buy-in you need to introduce AI successfully and unlock your organization’s full potential.

If you’re looking to adopt new technologies into your organization, contact us today to find out how we can help. 

About the Authors

Linda Lamppert
Linda Lamppert has worked for over twenty-five years in the field of human performance technology helping clients improve the overall performance of their organizations and employees. In addition to a strong background in instructional systems design, she has over twenty years of experience designing and delivering solutions for companies implementing traditional ERP and cloud-based systems. Linda’s solutions typically include blended learning approaches, training and systems documentation, online performance support, documentation of policies and procedures, business process reengineering, and change management. Most recently, she has been focusing on the people-related challenges associated with global process and system transformations as well as integration of mobile and micro learning strategies to streamline platform adoption.
Julyan Lee
Julyan is the Organizational Change Management Practice Lead at GP Strategies within Platform Adoption. His focus is on executing the OCM disciplines of Prosci, ADKAR, SAP Activate, Infor IDM Methodologies in both waterfall and Agile project environments. He is responsible for building GP standard OCM processes and methodologies, and ensuring uniformity in their application across OCM resources and their projects. He also supports business development teams in their sales pursuits, in formulating OCM solutions and proposal responses, and presenting to clients.

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