Rebuilding Organizations for AI

A successful AI transformation depends on many factors, but the right culture is a key component. Leaders should build a culture that promotes curiosity and experimentation while also creating guidelines for ethical AI use.

It’s also a good idea to start upskilling employees and creating training programs so that when AI integration becomes business as usual, they are prepared.

1. Start with a clear vision

Before AI can drive change, leaders must have a clear vision of what success looks like. They should identify business objectives that will be most impacted by gen AI and choose tools and vendors with proven experience in solving those problems. They should also create a data strategy, assessing whether or not new or existing data and datasets are required to effectively fuel AI systems.

They must then demystify gen AI for employees by explaining how this technology will help the organization achieve its goals and why it’s being implemented. They should also introduce mechanisms to manage uncertainties about gen AI where these arise (e.g., how to handle the risk of bias in AI models).

Once a clear strategy is in place, leaders should build out their team and infrastructure. They should develop AI-specific training programs and other learning opportunities, recruit staff with the necessary skills, set up an AI governance framework, conduct impact assessments and formulate policies, and redesign processes to enable the implementation of AI. This can be a time-consuming process, but it’s essential to the successful integration of AI in an organization.

The most resilient organizations will be those that are agile enough to adapt rapidly as business environments shift and evolve, ensuring they have the capacity to survive and thrive in any environment. They will need to acquire resilience in the form of an ability to learn, experiment and adapt – traits that AI can enable by accelerating change and empowering businesses to take action. The time to start building that capacity is now. By following these four steps, leaders can ensure that AI is not just a buzzword but a powerful driver of change in their organizations.

2. Create a governance framework

A robust governance framework serves as a guide for AI usage, setting rules and procedures for ethical, responsible and transparent practices. It should be updated regularly to address changes in technologies, laws, societal norms and other factors that may impact the way your organization uses AI.

To build a strong governance framework, you must first establish AI literacy. This involves elevating everyone in your organization to understand the capabilities and underlying principles of AI as well as its risks, ethics and responsibilities. This includes creating educational programs for employees at different levels of technical expertise. You should also map all AI systems across the enterprise, including third-party and AI-as-a-service tools, so that you can identify their owners, internal stakeholders, data sources and dependencies. Mapping AI systems will help you set appropriate policies and procedures for their use.

Governance structures should include clear policies on how to handle and respond to issues, including a process for reporting AI-related incidents or failures. It should also contain accountability mechanisms that hold individuals and organizations accountable for any negative impacts caused by their actions or decisions. Transparency is another important factor, allowing the public to see how AI works and how it makes decisions. It should be achieved through a variety of measures, including providing clear documentation, open-source code and testing and validation processes for models.

Many of these governance structures will need to be managed by teams, which requires strong leadership support. This will enhance data quality, security and management while fostering a culture of continuous integration and data ownership. Efficient top-down communication is also essential for this bottom-up strategy to succeed. It will also allow teams to track how an AI model is making decisions so they can identify biases or other vulnerabilities.

3. Reskill employees

Amid the growing demand for AI skills, companies should invest in reskilling employees. This proactive approach to employee development ensures that your team remains adept at their jobs and is essential for a digital future.

While reskilling can be time-consuming, it can also be cost-effective when done right. In fact, a recent survey found that high performers are investing 1.5% of their annual budgets in reskilling programs. In addition, reskilling can boost employee morale and confidence. This is especially important when you consider the impact of AI on the workplace, with the World Economic Forum predicting that 44% of jobs will be disrupted by 2023.

Before launching an impactful upskilling program, leaders should first assess their existing skill sets. They should determine what capabilities they have and which ones are missing, as well as how AI might change their roles in the future. This will allow them to focus on retraining their team members in the areas that are most relevant for their work.

For example, an experienced software developer who has built solutions for the commercial real estate industry may be a good candidate to train in machine learning and natural language processing. These skills are likely to become more important for their job, as they will enable them to leverage generative AI and develop new applications for the technology.

In addition, leaders should foster a culture of lifelong learning in their organizations by offering incentives and growth opportunities to encourage employee development. This can help to make the transition to an AI-centric workplace more manageable and less stressful. It will also empower employees to develop the necessary skills to collaborate with their artificial intelligence counterparts, further enhancing their productivity and boosting business outcomes.

4. Create a collaborative culture

To successfully implement AI, it’s essential to establish a culture that values creativity, adaptability, and collaboration. This will empower employees to challenge conventional thinking and explore new avenues of thought, driving groundbreaking AI solutions and pushing the boundaries of what’s possible. One best practice for creating such a culture is to prioritize people-centricity and align everyone toward a single objective. This creates an environment of trust, psychological safety, and teamwork that unleashes the full potential of both humans and AI technologies.

To do this, leaders should foster a learning mindset by encouraging risk-taking and embracing failure as an opportunity for growth. It’s also important to set clear ethical guidelines that promote responsible AI development and deployment. This will ensure that the company can safely leverage AI while avoiding the dangers of bias, privacy violations, and security risks.

Another important step is to build a data team that will support the implementation of AI. The team should consist of business administration and IT/AI engineers who will collaborate on the AI project and share expertise across departments. This will help to avoid siloed approaches and the reliance on intuition in decision-making. It will also enable the organization to take a more holistic view of the business and identify opportunities for improvement.

Finally, it’s crucial to determine the existing technological infrastructure and whether or not the AI solution will require additional hardware or software. Then, create a plan for gathering the necessary data to fuel the AI project and build a governance framework for its management. Lastly, the leader should prioritize the most pressing issues for AI implementation and make decisions based on their impact on the business.

5. Embrace change

Amid the uncertainty that AI presents, leadership must make resilience and change management practices an integral part of the transformation. This means fostering open channels of communication and encouraging a team culture of adaptability and collaboration. It also means identifying and supporting early adopters who can serve as champions for the organization’s new AI-driven strategies.

The most effective way to manage AI implementation is to socialize the technology early and provide training that’s relevant to each stakeholder group. This allows people to get accustomed to the technology on their own terms, making it more likely they’ll embrace it. Moreover, socialization and training must continue throughout the AI rollout. This keeps people informed of progress and helps them adjust their expectations based on what’s been accomplished so far.

Lastly, leaders must recognize and celebrate small wins. Acknowledging milestones and recognizing employees who have shown a strong commitment to the change can help boost morale and build momentum. This will motivate teams to keep up the good work and push for further advancements in their AI initiatives.

In addition, leadership should encourage middle managers and early career professionals to drive change from the bottom up. This is important because many of them are in positions of formal authority and can influence their peers. For example, by embracing consumer-grade AI tools, sharing granular successes and taking risky projects without seeking permission, they can set an excellent example for others to follow.

Embracing AI may feel like a daunting task, but it is an essential one if organizations want to survive the disruption that it will bring. By implementing clear vision, governance frameworks, upskilling employees and creating a collaborative culture, companies can ensure they are prepared for the next wave of technological advancements.