Artificial Intelligence (AI) isn’t simply fodder for the great storytellers of Westworld, AI, and Terminator anymore.
In the real world, AI can offer unprecedented capabilities for integration and development, unlocking a slew of practical business and commercial applications, through Artificial Intelligence Software and AI development.
The term Artificial Intelligence encompasses a wide range of intelligence, but essentially is a computer science focus in developing machines or software that possess human intelligence. And that’s a really wide range, encompassing tasks from basic calculations to the self-steering technology making headlines as transportation giants test out the technology.
While immediate innovations unleashed by AI may not be as flashy, they aren’t isolated to a single industry. Instead, through Artificial Intelligence Software, businesses of any size and in any industry can leverage and understand their big data, boost customer engagement, and amp up organizational efficiency.
What is Artificial Intelligence Software?
Thanks to AI, interaction with computer software can be much more user friendly. Because AI aims to mimic human thinking, a computer program that leverages AI can answer generic questions, connect pieces of information, and even modify information without impacting entire programs. In other words, thanks to AI, accidentally hitting a wrong key shouldn’t result in hours of comping for a misplaced or deleted computer file. And that’s possibly the least thrilling example of all.
Thanks to machine learning, AI can unpack massive volumes of data – in organizational communications, in social media, in customer interaction records, analyze it, and present a response an organization can act on. Not only does this unpack a wealth of information that can boost revenue, it saves on expenses when an organization isn’t paying a person – or many people – to manually slog through an impossible mountain of data.
Artificial Intelligence Software offers several transformative commercial and business applications, including:
- Automating workflow, to leave your human employees to add their professional expertise instead of clicking extra buttons
- Keeping customers happy, with full availability even when your human employees are sleeping
- Intelligent listening, to really understand tone and conversation across employee and customer interaction through the use of intelligent chat bots
- Personalization, to better respond to consumer based on a real understanding of actual customer sentiment
The numbers suggest Artificial Intelligence in business is already heavily adopted. In fact, according a 2018 survey from Narrative Science, AI adoption grew over 60% in the past year, and in 2017, 61% of participants said they had already implemented AI.
Getting on Board: Artificial Intelligence Development at any Organization
For organizations just considering or delving in AI, the subject can feel like a trendy buzzword with little practical application. Software development experts can assess your business needs and offer guidance on where AI fits within your organizational objectives and goals.
Forbes technology writer Gil Press argues that AI is not just a “reigning buzzword,” but a set of technology primed to help organizations transform data into informed, practical actions.
To prime the organization for AI development, business leaders should keep these factors in mind:
- The bigger, the better. The only thing equipping the artificial with “intelligence” is data – gargantuan amounts. As a result, software development should produce a product that can collect, process, and analyze massive datasets (“big data”) in real time.
- Head to the cloud. All that learning data will need a place to live, and this place is most likely commercial or corporate cloud storage, which negates the need to invest in costly, powerful servers to move the AI through the learning phase.
- Expect immediate results. Enterprise AI applications may vary, but all require real-time responses and results. Example applications include:
- Chat bots
- Smart houses
- Fraud detection
- Facial recognition
- Translation (ie: Google translate)
- Voice recognition
- Intelligent digital personal assistants (ie: Siri)
- Product suggestions
- Don’t stop at an algorithm. Not unlike human learning, AI isn’t simply a “set and forget” technology. A successful AI integration will leverage robust data sets to avoid bias and low quality training that can result from limited datasets. Machine learning can be unguided, or companies can guide the process by supplying both the data and the desired output. The approach is established by each organization. One key rule to remember: AI should be practical. During training and planning, organizations should plan to integration AI systems into standard business practices so it can efficiently input and output data as part of the workflow.
- Stay current. Organizations will need to continuously engage with and train their AI to adapt to changes, whether than change is an entirely new purpose or simply minor adjustments that reflect necessary output changes based on trends in the business environment.
- Stay connected. As with any aspect of a business, organizations need to check their AI’s work. Either through a second AI system or a human employee, decisions generated from an AI system need verification to understand, correct, and control mistakes.
With its broad suite of applications only slated to grow with cognitive abilities on the horizon, AI should be part of every company’s success strategy.
And, just as we’ll be waiting for new developments with the AI cowboys-gone-rogue on Westworld with baited breath, competitive organizations don’t want to fall behind AI in the real world – it may be much more costly than catching a few spoilers in a newsfeed.
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