Artificial intelligence has been a hot topic for businesses for quite some time now. Two years ago, more than eight in every 10 companies think that AI is a priority for their business strategies. AI, they felt, helps them get a competitive edge.
According to another report, this time coming from PWC:
- 20 percent of businesses are planning to deploy artificial intelligence for their entire enterprise
- 27 percent have already implemented AI in more than one area of their business
- 15 percent are currently planning to expand implementation in multiple areas
- 16 percent have already implemented pilot AI projects
- 22 percent are currently planning to use AI
The future is bright for artificial intelligence. In 2018, McKinsey & Company estimated that AI would add around $9.5 to $15.4 trillion to the world’s economy.
But AI Is Failing to Impress
Imagine grooming a child-singing prodigy for years only to have his voice break while singing the first song at his international debut concert. That is what’s happening to artificial intelligence right now.
It’s difficult to imagine how AI may disappoint businesses. According to a survey done by Boston Consulting Group and the MIT Sloan Management Review, around seven out of 10 companies are not seeing value from AI projects.
Around 40 percent of the companies that they surveyed reported significant spending and investments in the technology but reported no business gains. Another study shows that a good 85 percent of AI projects fail.
Why is this happening? It’s because businesses are only piloting AI and not doing more with it. They use it as a single business process.
What do businesses need to do to succeed with AI?
Businesses need to start spending resources and time on changing the way they work. They also need to transform their own culture, which will help bring artificial intelligence up to the scale where it can give meaningful and significant results. With these changes, every AI project will have widespread use in the company.
To do this, you need to:
1. Move away from filtered information to enterprise-wide collaboration.
Companies that succeed in their AI projects bring together their business, analytics, and operations experts together. This helps produce different perspectives that will guarantee the needs of the entire organization are addressed early on.
2. Drop experience-based and leader-driven decision-making. Choose to make data-driven decisions, instead.
The best business decisions should be made by humans who factor in their own intuition and judgment into the process but also relies on the recommendations made by AI algorithms. This way, the company is making decisions that no human or machine can arrive at on their own.
3. Embrace experimental, agile, and flexible mentality.
AI is groundbreaking, earth shaking, and game changing. Being rigid and risk-averse will only stop your organization from taking full advantage of AI’s fullest capabilities. You should instead be bold, adopting the test-and-learn culture that will be crucial in creating a viable product in a couple of days or weeks instead of months.
It’s not going to be easy, but here’s what you can do
These are the changes that need to happen at your organization if you want AI projects to succeed.
People naturally resist change. That’s just human nature. A company that has been successful doing something in the past will always try to look at what worked before and believe that it will work again for every single case in the future.
But here’s the thing, AI is not anything like you have used in the past. It’s something new, and the natural reaction would be to test it out first on a small and limited scale. But that does more harm than good.
The shifts that need to happen aren’t going to be easy. Here are some ways that you can make it less painful.
Set the Stage for Success
Businesses should include their employees on board with their AI projects, and pave the way for headache-free AI initiatives. Business leaders can make this happen by explaining to stakeholders and employees what AI is all about and how employees fit into a new AI-centric culture.
Know in advance what’s going to hinder change. Then, remove these barriers.
You should have the budget for both AI adoption and integration.
Planning for different AI projects should take into consideration each initiative’s feasibility, the investment required, and its value to the organization. You should be able to identify similar or complementary projects and combine them so that you get the most out of these AI initiatives.
Assign roles and responsibilities appropriately.
Businesses who succeed in their AI efforts should focus on being able to figure out who owns the work and how these are going to be executed.
When creating teams, you should have both an analytics group and a business group working for the same team. Each group will be tasked with their own sets of responsibilities. For instance, data governance, system management, and AI recruitment are better handled by the analytics group.
However, when execution happens, the entire team will be accountable for the results.
Educate and train everyone about AI.
It doesn’t matter if you’re the CEO or you’re an assistant in the accounting department, you should know what AI is and how it works. More than that, you should be familiar with AI tools and how to use them.
Everyone in the organization should have a complete understanding of how artificial intelligence can help and what it can do. What’s more, all employees are expected to develop soft skills to use AI tools in their everyday tasks.
Reinforce the shift towards artificial intelligence.
As you go through each change and every process, you should keep the momentum at high speed. Most AI transformations take a long time, with some lasting up to three years. It’s easy to be enthusiastic at the start, it’s going to be a bit difficult a year after.
How do you reinforce the AI-focused changes?
- Make sure that your leaders are also good role models.
Employees will be looking at business leaders and pattern their behavior to theirs. For instance, they will probably find an AI seminar a waste of time if you’re C-suite executives never attend them.
- Track adoption to see who is lagging behind and how they can be helped.
- Give out incentives to those who excel and embrace the change.
For example, you can honor the employee who has helped make your AI projects a success.
Photo courtesy of Stuart Rankin.