March 27, 2019
Why Do Some Organizations Struggle to Adopt AI Technologies?
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Artificial intelligence (AI) is without question one of the most talked about technologies of recent years. Regardless of industry or country, organizations across the planet seem to be talking about AI and what it could do for them. And rightly so; the future is full of infinite possibilities, and 2019 is set to be an exciting time for the AI industry.
Positively, many businesses are starting to take note of AI’s growing momentum – MMC Ventures’ recent report found that AI adoption has tripled over the past 12 months, while one in seven large companies has already adopted the technology.
It should come as no surprise that large tech enterprises are readily embracing AI as a means of improving the way they operate and their ability to engage with clients. However, for smaller organizations and companies that are less tech-savvy, the ability to identify and implement AI can be overwhelming and complicated in equal measure.
Recent research in the UK by Microsoft revealed that while 41% of business leaders acknowledge they must radically change the way they work within the next five years, over half (51%) do not have an AI strategy in place to address those challenges.
The question beckons: what are the main barriers stopping organizations – particularly those outside of the tech sector – from taking advantage of this powerful technology? Based on our experience supporting the development of AI solutions for different organizations, we have identified two key barriers.
The first barrier concerns a general lack of understanding about what AI actually is. For many companies that don’t provide a primarily tech-based product or service, it can be difficult to understand what terms like machine learning, deep learning or natural language processing mean, let alone how such tools could be used to improve the way they operate. But the important point here is that the benefits arising from AI are not limited to tech companies.
AI in its most basic form refers to the simulation of human intelligence by machines. As such, the technology is naturally geared to take on mundane and time-consuming tasks, such as data processing. AI can analyze huge amounts of data from a wide range of sources, establishing the outliers and trends in real-time and then recommending potential actions. This application is relevant for the majority of industries, be it a recruiter compiling a list of relevant candidates based on their CV, to a healthcare company reviewing patient blood samples.
The second factor is the obvious skills gap between tech and non-tech companies when it comes to understanding the latest digital trends. After all, the former has access to IT experts that are key to driving innovation; by contrast, the latter can often find themselves relying on outdated IT infrastructures and poor in-house tech nous.
But even this (seemingly) major problem has a simple solution. Non-tech organizations are encouraged to look to startups who have a strong understanding of technical toolsets like machine learning and natural language processing. By engaging with third-party AI specialists, they can develop a greater knowledge of just how they are positioned to reap the benefits of AI.
Moreover, companies don’t necessarily have to build the technology to benefit from it. Nearly half of the companies surveyed by MMC Ventures favor buying AI solutions from third parties who are more adept at developing these tools.
Ultimately, we are only beginning to discover the full potential of AI. As the capabilities of this technology continue to develop, I have no doubt that tech and non-tech enterprises alike will understand and embrace the benefits it offers. But it is also up to companies like Fountech.ai to ensure there is widespread industry awareness of AI’s potential, and how it can be used to better the performance of organizations, regardless of their industry.
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