Artificial Intelligence and the Enterprise - Smarter With Gartner
- Updated on: 2017-06-09
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The exceptional opportunity of AI makes it imperative for enterprises to plan for change.
Artificial intelligence (AI) technology promises to solve problems organizations could not before because it delivers benefits that no humans could legitimately perform.
AI offers the means to maintain optimum efficiency and proficiency to meet customer demands. CIOs,chief data officers (CDOs), application development leaders andenterprise architects, among others, must be willing to explore, experiment with, and implement, AI capabilities to pursue new value generating opportunities.
AI is becoming more common. In fact, by 2021, Gartner projects that 40% of new enterprise applications implemented by service providers will include AI technologies.
To better understand how businesses should shape their AI strategy, we spoke withMike Rollings, research vice president at Gartner, to gain his insight into trends shaping the future of AI and what businesses should consider in AI implementation to remain competitive in the market.
A: AI is not defined by a single technology. Rather, it includes many areas of study and technologies behind capabilities, such as voice recognition, natural-language processing, image processing. These technologies and capabilities benefit from advances inalgorithms, abundant computation power, and advanced analytical methods like machine learningand deep learning.
CDOs will immediately recognize that in order for AI to reach its full potential, they must develop greater organizational competency in data sciences and assure thatdata and analytics can be relied upon for various insights. This includes involvement in the assessment of frameworks, software and services claiming AI capabilities. They will also need to work with application development leaders to enable applications that can change behavior based on the flow of data and events.
A: Right now, the industry that is the most excited about AI implementation is the financial services sector. CDOs in this industry are dealing with a very large amount of data in the form of financial transactions that must be analyzed for fraud, or customer behaviors that provide insight into what type of financial advice would be most beneficial. Another industry is healthcare where insights generated frommachine learning are improving discovery, diagnosis, care delivery and patient engagement.
A: For AI to be effective within an organization, CDOs must help establish adata-driven culture – information as a second language, if you will. They may also be faced with impacts in the areas of talent sourcing; skills development and training; organizational structure; analytical methodologies; analytical tools; data acquisition and monetization; algorithm acquisition/creation; analytical modeling; analytical model training and maintenance; and process adaptation.
They may also need to create a skilled team ofdata scientists, data engineers, statisticians and domain experts who can manage the complexity of data, analytical methods andmachine learning associated with AI, and help apply it with workers, customers and constituents.
Without these skills, enterprises will not himplement effective AI into their IT ecosystem. To avoid the pitfalls of the skills gap, CDOs should invest into their existing employees to develop both their creative and analytical thinking skills as AI implementation requires both.
Client Research Gartner clients can read more about the future of AI in“Develop Your Artificial Intelligence Strategy Expecting These Three Trends to Shape Its Future.”
Gartner Symposium/ITxpo 2017 Learn more about AI trends atGartner Symposium/ITxpo 2017. Follow news and updates from the events on Twitter using#GartnerSYM.
