According to Gartner, 59 percent of companies have already deployed artificial intelligence and machine learning and many intend on doubling the number of AI projects they’re working on within the next 12 months. In fact, by 2022, most organizations will have an average of 35 machine learning or AI projects in place.
Underpinning this trend is the simple fact that a growing number of companies see AI adoption as critical to their long-term success. Early adopters, for example, view it as a path to gaining important operational advantages. Meanwhile, for those who have lagged behind, it’s essential for remaining competitive.
Among the many other reasons why business leaders are adopting AI, as noted in a recent survey from AI Trends, include enhancing customer experiences, improving existing products, making more strategic and informed decisions, and optimizing internal operations. Ultimately, many view AI as the key to making better decisions, faster. That’s true across virtually every industry, including advertising and marketing, banking and insurance, retail, travel, and media and entertainment, among many others.
Different areas of focus
So where are companies focusing their attention when it comes to AI? A variety of different places, as it turns out. While IT automation and cybersecurity are at the top of the list, forecasting and marketing optimization are also growing areas of investment, cited by 19 percent and 16 percent of respondents, respectively. Looking ahead, both of these areas will become increasingly important, with 27 percent of respondents looking to implement forecasting over the next 12 months, for example.
Other areas where companies are investing in AI include customer service, virtual assistants, quality control, and sales optimization. To bring these initiatives to life, they’re using cloud-based AI and opensource development tools, while also working with strategic partners.
Not all paths to AI adoption are equal
Despite the fact that businesses are increasingly adopting AI, not all are having success implementing it. Among the reasons why include their failure to embrace the core practices necessary to support widespread adoption. Meanwhile, cultural and organizational challenges are also considerable roadblocks.
Another major challenge many companies face is having misaligned expectations. Leaders tend to underestimate the work involved in moving from discrete, highly focused AI pilot programs to enterprise-wide strategic initiatives designed to tackle major business challenges. Not only that, they often have unrealistic expectations about what results they can expect and in what timeframe.
As if that weren’t enough, for many businesses, legacy practices can get in the way. Harvard Business Review notes that these practices include the tendency to work in silos when collaboration is critical, relying on experience to make decisions rather than data, and being too rigid and risk adverse when in fact companies need to be agile, experimental, and adaptable.
The right way to integrate AI
AI is estimated to add $13 trillion to the world’s economy over the next 10 years. For enterprises looking to take advantage of that tremendous upside, while also optimizing their business, delivering better customer experiences, and differentiating themselves from their competitors, it’s important to take the right path to adoption.
While making internal investments to support AI initiatives is critical, in many cases, the best way forward isn’t to go it alone. Rather, by taking a hybrid approach that combines both building and buying AI systems, companies can position themselves to get the best results in the shortest amount of time.
Make no mistake, many of your competitors are already adopting this approach. The question is, are you?
If you want to find out whether you’re AI-ready and see if your business can benefit from this technology today, feel free to get in touch—we’re happy to help!
-p-500.jpeg)
