In reviewing the AI-specific data from our Work Ahead series, it becomes clear that organizations face a pressing need to rethink the systems, processes and skills required to compete in markets that are more competitive than ever.  

From the factory floor to the back office to the boardroom, many of the tasks that people undertake today would be done better through the application of AI and other systems of intelligence.

In order to leverage AI in your work ahead, the following steps are important to consider and act on: 

Check your progress with AI by checking the growth of data. To stay ahead of the curve, businesses should set a target for the next 12 months to match their decision making speed to that of anticipated growth in data volumes. For instance, if you expect a 30% annual growth in data over the next 12 months, then the organization’s speed of making insights and applying AI needs to accelerate by 30% during the same period. Anything less will impact the speed of doing business in this fast-changing world.

Be ready to kick off your own skills renaissance. Every business now needs big data specialists, process automation experts, security analysts, human-machine interaction designers, robotics engineers, and machine learning experts. As a result, these skills aren’t easy to acquire. In addition to having sophisticated hiring and retention plans, organizations need to work harder to leverage the talent they already have. A root-and-branch reform of upskilling and internal career progression is an important element of the multi-factor HR strategy necessary to succeed at this foundational task.

Get your data right, and make it richer. Ensuring your data is in good shape isn’t enough; businesses also need to bring in richer sets and types of data, such as psychographic, geospatial and real-time data – all of which have the potential to drive higher AI-centric performance. Managing this data and making it useful for interrogation and leverage by AI systems is an important step on the road to digital maturity. Without this unglamorous hard work, a lot of data will remain noise and never reveal the signal buried within it.

Adopt a culture of collaboration and learning. Organizations need to spread the mantra of data and AI across every aspect of their operations – not just keep them caged within the IT department. This “spreading of the gospel” can start by establishing data tribes with squads of data stewards, data engineers and data modelers swarming around a specific challenge or customer touchpoint. Executives across functions – not just in IT – should institute a digital culture in which every employee is eager to use and apply these new data services within their roles. Rotating IT staff and non-IT staff between functions – IT and non IT – is an important tactic that can easily be deployed.

Solve the human side of the equation. AI is not just about technology – in fact, it is more importantly about people. Critical to leveraging the possibilities of AI is hiring talent that can understand the technology and business needs and create solutions, not just build models. Organizations should deeply focus on HR plans (hiring and retention) that prioritize securing the next generation of talent; without it, it will be virtually impossible to keep pace in markets that are being disrupted at light speed.

Construct new workflows to reach new performance thresholds. Organizations should start by reshaping the jobs of today into the jobs of the future by establishing the trust needed to make human/machine teaming a reality. The trick is preparing your workforce for these profound changes in how they work. Without this trust, many individuals and groups will see new machines as a threat to their job security rather than a protector of it.