Mobility has been one of the defining characters of the last decade and while its impact in consumer space is widely visible, the behind-the-scenes shifts in enterprises have been equally transformative. But as mobility starts to saturate, an entirely new technology is ready to propel the next phase of innovation- AI. As per a Gartner study, by 2021, around 40% of enterprise solutions would use AI at some level.
And while we can?t comprehend the full-scale of its adoption, there are some key areas that would see the first wave of transformation. Here are just a few of them:
Internal operations of any enterprise depend on a whole range of mobility solutions- from employee attendance and project management to payroll generation and internal communications. The AI-driven solutions in the coming years would not just keep each of those applications in sync but also continuously monitor their activities to flag any anomalies that are simply too tough for humans to detect. Be it an unusual spike in data traffic or simply optimizing the system by adapting to the usage pattern, AI would form the first line of defense in future enterprise solutions.
It won?t be an overstatement to predict that within the next 5 years AI-enabled solutions would be presiding over the board of any organization for all crucial decisions. While most of the enterprises currently take decisions based on statistics and sheer hunch, as improved data mining and predictive analytics become cheaper and more accessible, it would take any uncertainty out of the decision-making process. For instance, most of the stock trading enterprises already use some kind of AI tool to decide their portfolio and even automate the trading. It?s only a matter of time before such tools are deployed in other industries as well.
BYOD policy is increasingly gaining popularity and it is reasonable to expect that within a few years, a majority of employees in any given enterprise would be working on their own devices. And you may already know, the smartphones already feature AI-enabled chips that drastically improve performance. Yes, this isn?t exactly enterprise solutions adopting AI but rather adapting to it. But in any case, the applications would be built to make the most out of these improved capabilities.
Be it the recent surge in chatbots, AI assistants, or simply the recently unveiled Google Duplex, AI has been penetrating the communication space for quite a while and it?s now mature enough to be inducted in enterprise solutions. Not only they offer a much faster, reliable, and scalable solution for businesses to communicate with their clients but their advanced features like detecting emotions through voice and face can be a ground-breaking tool for enterprises to build the most effective communication channels with their customers and within.
But as always, these exciting transformations have their own hurdles. They aren?t too high to derail the process but certainly have the potential to delay them.
Perhaps the biggest threat to mass AI deployment is not other technologies but the overenthusiasm of AI itself. Many enterprise mobile solution providers often market simple algorithmic processes as AI. This kind of misrepresentation would essentially disappoint the early adopters and thus discourage further investment and by extension, adoption.
For example, though Face detection or text-to-speech might seem like AI-capabilities to some, they are essentially routine algorithmic tasks. It is actually the Face Recognition or understanding the semantics of the text or speech that makes an application truly AI-enabled.
AI is often portrayed as the mortal enemy of the human workforce and there is quite an anxiety about vertically integrating such technologies into any enterprise. But the organizations who are already working with such solutions have an entirely different experience. Yes, a few mundane jobs are lost but far more productive posts are opened up. But this requires a complete operational restructuring- an inertia that many enterprises might find tough to overcome