How Artificial Intelligence Can Make Your Organization More Resilient to Change
Artificial intelligence (AI) is one of the top investments in organizations across the world. From simple chatbots to complex finance tools, there seems to be no end to the power of machine learning and artificial decision-making. It also plays a role in big picture issues, assisting with change management, crisis reactions and risk assessment.
Discover how you can directly — and indirectly — use AI to improve your processes and make your teams more resilient.
AI Tools Evaluate Information and Provide Solutions
From an immediate risk management standpoint, AI can evaluate different options within a company and give managers ideas on how to move forward with a project or plan.
“Artificial intelligence can boost our analytic and decision-making abilities by providing the right information at the right time. But it can also heighten creativity,” write H. James Wilson and Paul R. Daugherty, coauthors of “Human + Machine: Reimagining Work in the Age of AI.”
They surveyed more than 1,500 companies to learn how AI and humans work together, and use the example of a product designer submitting a list of desired features to software that uses AI in the invention of form. It spits out dozens of ideas, from which the designer can choose and improve upon. The creative inspiration provided by the generative design software like Autodesk’s Dreamcatcher sets designers up for success.
This project management example can also be used in crisis management. Adam Uzialko at Business News Daily says AI tools are adroit at coming up with courses of action and can analyze them for success rates. In a situation where human leaders are scrambling, AI tools can provide clear information and solution options. Decisions can then be based on data-driven insights.
That said, artificial intelligence isn’t really choosing the best solution (or even presenting the best option) but rather evaluating solutions and options based on the data provided. It’s up to human leaders to decide the best course.
“Machine learning models can help users understand the states through which an asset transitions on its road to failure, and in doing so make predictions about the probability of failure at some future point,” explains solution architect Aaron Forshaw.
“Those predictions can be hugely valuable, but as a human being who must make a decision about that asset, I need to place that prediction in the context of multiple dimensions such as finance, criticality, human resources, regulations and laws, and other organisational objectives and constraints,” he writes.
In other words, while a model might recommend pulling a project due to potential failure rates, human change managers know that isn’t always the best option, and other solutions need to be considered and applied first.
The team at Azati software even asked whether or not AI could replace the C-Suite, middle managers or front-line leaders. They admit that while AI tools can replace certain tasks, these software options will more likely turn managers into leaders — or directors who can guide their staff.
The Azati team also cites an Accenture study which found 84 percent of managers say they expect AI to make their jobs more effective and interesting. This is because AI allows them to be more focused on decision-making and guidance, rather than data analysis and information gathering.
Artificial Intelligence Across Your Organization
In order to be successful, AI tools can’t be piecemeal. One team can’t use a system that another department thinks is too advanced — and two systems can’t afford not to speak to each other. This isn’t good for management and it won’t make your team resilient to change.
Jesper Schleimann, digital transformation officer at SAP, says AI incorporation needs to have “musicality,” where technologies work for employees, managers and HR. Organizations that are typically siloed will have a harder time accomplishing this. It’s worth the effort, though: When AI tools work together across an organization, operations are streamlined and better able to be adjusted.
Still, many leaders aren’t ready for AI to be part of their teams. Business journalist Jared Lindzon looks at a study by Deloitte of 10,000 HR and business leaders in 140 countries. It found while 41 percent of organizations have fully implemented (or made significant process) in adopting AI tools, only 15 percent of executives said they were ready to manage a workforce with people and AI working side by side.
For leaders to develop truly flexible and change-resilient organizations, they need to stop viewing AI as part of the IT department and start treating these robots as valuable assets across the board.
“AI is no longer some kind of ‘gee whiz’ technology, but increasingly a key to competing effectively in today's marketplace,” writes Greg Satell, author of “Cascades: How to Create a Movement that Drives Transformational Change.” “As the technology continues to evolve from complex integrated systems to a modular stack, even small and medium enterprises will find that they need to adopt these capabilities or fall behind.”
A unified system will make it easy to enact change, and also ensures that every team and department is on the same playing field with the information and resources available to them.
AI Indirectly Helps Your Change Management Efforts
While artificial intelligence can be part of your change management process, your investments may already be paying off without you realizing it — or there may be ways to make your AI tools work for you.
Nick Genty, cofounder and CEO of AgEYE Technologies and Iconic Solutions, says technology and machine learning will make businesses more mobile, allowing employees to work remotely. Not only will AI tools help with the management of tracking these workers, they will also allow companies to recruit better employees. This means directly managing (or micromanaging) their employees will take less time, so leaders can focus more on big picture strategy.
Virginia Engholm at the HR Certification Institute, agrees. AI technology improves employee retention through better training, she writes. Plus, AI tools can remind managers about training investments or highlight employees that could benefit from a new challenge. These steps keep employees engaged — and keep their institutional knowledge within the company — while upskilling them.
During a crisis, these are the employees you want to have on hand: highly-engaged, highly informed and with the right skills to jump in and solve problems.
“AI and machine learning allow you to create personalized learning experiences so employees can learn at their own pace, based on their own needs,” explains executive coach Rhett Power. “Herding an entire department of people into a one-size-fits-all training session is inefficient. Different people struggle with different responsibilities. Likewise, some need more help with certain aspects of their jobs than others.”
AI tools made for other purposes can also make your company more resilient. For example, financial journalist Eric Rosenbaum interviewed the CEO of IBM on their AI tool which predicts with 95 percent accuracy which employees are about to quit. The system also makes recommendations for retention, so the company can reduce turnover. If a company can anticipate higher turnover levels or identify problems within certain teams, it can take steps to prevent gaps in production before they arise.
Your Company Needs the Right AI Tools to Succeed
Artificial intelligence on its own can’t save your company or make your team hyper resilient. You need to choose the right tools and make sure that their adoption and use is unified across your company culture.
One of the biggest challenges that AI faces is accuracy. Mary Shacklett, president of Transworld Data, used the example of an AI system that reviewed 100,000 simulations to predict the 2018 FIFA champions. Itl selected Spain, Germany and Brazil; the actual top three were France, Croatia and Belgium. While this is a fun example, it shows how AI can’t be relied on as the only source for information.
Shacklett says AI is only as useful as the data and predictions it puts out, which is why companies need to constantly check their accuracy by reviewing data accuracy, running tests and redoing simulations to make sure the information the tool puts out is realistic.
Knowing your data is one of the most important parts of choosing or implementing AI tools, says SaaS entrepreneur Rajat Harlalka. Some tools look at large sets of data, while others can work with less information. Plus, making sure the data is reliable and accurate is at the core of your tool’s success.
Additionally, the AI tools themselves also need to be flexible and adaptable. “For machine learning to make a difference at the enterprise level, deployment at scale is critical and making post-production deployment of models easy is mandatory,” writes the team at Algorithmia.
As more AI tools and software solutions enter the market, companies can choose what works for them and what features they need. They can find tools that learn and adapt to truly help out during a crisis — or even through basic changes.
Keep these elements in mind as you adopt whatever AI tools you need for your business. The investments you make today will determine your competitiveness in the market — but also your internal resilience and handling of change. “Take the time to do your research and find an AI vendor that combines sophisticated software with a practiced methodology for implementing them,” advises Jeff Catlin, CEO of analytics solutions provider Lexalytics.
You need an artificial intelligence tool that meets your needs, but doesn’t blow out your budget or take years to implement. Only then will you glean the value you need for your overall organization.