Towards the end of 2016 and in the beginning of 2017, we have seen so many technology predictions by market watchers. One of the most promising technologies pointed out by them was artificial intelligence or AI.
This is because of the growing interest as organizations recognize the potential of AI to disrupt business. AI includes technologies such as deep learning, neural networks and natural-language processing.
Market research firm Gartner says that by 2020, 20 percent of companies will dedicate workers to monitor and guide neural networks.
The firm notes that the idea that AI technologies can be delivered as finished products without further human investment is a recipe for failure.
While older rule-based systems could be set up, configured and then ignored for a few years, neural networks need to be retrained whenever new data is available, which is essentially constant.
In fact, neural networks only maintain value to the enterprise in an endless retraining and reinforcement loop. CIOs will need to make the business case to ensure the project is provided with necessary resources.
This will require new skills and a new way of thinking about problems. Those with backgrounds in design, data science and logic might be better prepared than programmers who tend to think in more structured approaches.
Additionally, neural network responsibilities will be spread across departments and within many applications. CIOs must ensure that IT owns the strategy and the governance of selected platforms.
Given the acceptance of disruptive technologies, there are chances for start-ups to overtake Amazon, Google, IBM and Microsoft in driving the AI economy with disruptive business solutions.
The reason is that many AI startups are owned by former employees of large vendors who leave and form a company focused on AI in a specific industry, or academics who have discovered their discipline is suddenly lucrative and exciting.
This means there are many packaged AI solutions that should be considered before an organization considers building a custom AI solution in-house. The packaged options require fewer resources and can be deployed faster.
AI can turn out to be disruptive in industries such as healthcare, where huge amount of data accumulates.
Therefore, CIOs should evaluate business processes to identify where AI could be beneficial for each enterprise.
Look specifically at underserved areas of the company that have very large amounts of data but lack access to analytics. These areas could benefit from the ability to augment and improve human decision making.