Applying AI in the Enterprise
Enterprises quickly realize that they need to incorporate artificial intelligence (AI) into their business processes. With the ever-increasing number of proof-to-concept and other pilot programs, as well as all the large-scale commercial deployments of AI in various organizations, this trend is only expected to grow. In fact, AI spending is expected to increase from $3.7 billion in 2017 to a whopping $80.7 billion by 2025.
Much of AI's success here is that many of its delegated tasks are data-driven, meaning that they are easily measured and benchmarked. Even during small pilot programs, AI technology will quickly prove itself and its benefits, only by looking at the performance data.
AI has the power to provide new insights, improve business outcomes, and transform the entire decision-making process within a given organization. With constant advancements made in computing power, algorithms and other such analytical methods, AI capabilities such as voice recognition, image processing, NLP are rapidly changing the face of the corporate landscape. New business models are being developed and implemented on an almost daily basis, thanks, in large part, to these disruptive technologies.
The AI Arms Race
“Breakthroughs in AI, enabled by new hardware architectures, will create new intelligent business models for enterprises,” says Nigel Toon, co-founder, and CEO at Graphcore.
“Companies that can build an initial knowledge model and launch an initial intelligent service or product, then use this first product to capture new data and improve the knowledge model on a continuing basis, will quickly create clear class-leading products and services that competitors will struggle to keep up with.”
With the rise of interconnected mobile devices, as part of the so-called Internet of Things (IoT), large corporations feel the pressure to innovate or risk becoming obsolete by sticking to the traditional ways of doing things.
Luckily for them, however, they can tap into their decades-long industry experience to develop and implement horizontal AI to streamline operations and significantly improve efficiency. Industries like automotive, retail, financial services, and healthcare, among many others, all stand to gain here.
This unstoppable digital transformation needs enterprises to come to grips with how to use data-driven AI. Knowing how to extract this data is a crucial element in maximizing the AI potential. Nevertheless, information is often misunderstood or severely underutilized.
The decision-making process will also see a drastic change in the immediate future. The technology that currently exists relies on deep-neural nets and millions of data points. Up until now, these expert-systems were not mainly fit for complex decision-making in dynamic and constantly changing business environments. It is set to change, thus moving enterprise AI from simple classifications to actual decision-making capabilities.
Data governance will, however, take center stage for the foreseeable future. As companies will begin to align their departments and corporate workflow around data, proper data management and security will prove themselves to be essential components of success.
By employing the help of disruptive tech specialists and establishing cross-departmental teams for training and experimentation, enterprises can successfully leverage these new technologies and exploit the full potential of both internal and external data coming in. Interested in learning more about applying AI in your enterprise? Contact us today!
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