Tag Archives: artificial intelligence

Artificial Intelligence and DaaS

3 Technical Innovations Ready to Drive Enterprise AI Adoption

Jun 24,2019 / By / No Comment

While we’ve discussed the disruptive power that artificial intelligence (AI) applications bring to enterprise organizations, the truth is that AI adoption is still low for these businesses. However, adoption level is at a tipping point; investment in AI has tripled, and recent technical innovations promise to make AI not just an underlying technology capability, but a fundamental business tool. Here are just three of the technical innovations that enterprises can use to better leverage the disruptive power of AI:

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Artificial Intelligence and DaaS

The 5 Elements Your AI Strategy’s Code of Ethics Needs

May 21,2019 / By / No Comment
AI ethics

As artificial intelligence’s (AI’s) potential grows, so does the need for a cohesive AI strategy to leverage AI to prioritize and execute the enterprise’s goals. Aside from articulating business goals and mapping out the ways organizations can use AI to achieve those goals, there is another extremely important element that every AI strategy needs: a code of ethics.

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Artificial Intelligence and DaaS Technologies

How to Create Your AI Strategy

May 6,2019 / By / No Comment
AI Strategy

For companies that are committed to creating Digital Transformation (DX) within their organizations, artificial intelligence (AI) is a critical component. The data that is created in DX initiatives has limited value if an organization can’t extract valuable, accurate, and timely insights from it. That’s why enterprise organizations are using AI technologies to pull actionable value from its data; in fact, by the end of 2019, 40% of all DX initiatives will be related to AI.

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Artificial Intelligence and DaaS

IDC’s AI-Based Automation Evolution Framework: a New Way to Think About AI Automation

Jan 9,2019 / By / No Comment
AI Automation Evolution Framework

In October 2018, a Reuters article informed the world that Amazon had scrapped an AI–based recruitment application that turned out to be biased against women. Most headlines about this story highlighted the company’s failure in developing an actionable and fair solution for one of the most important processes of the HR team.

However, what this and similar examples of today’s AI “failures” neglect to acknowledge is the complexity of end-to-end process automation based on AI technology. This complexity stems not only from current technical limitations but also from the immaturity of corporate policies, government regulations, and legal systems to deal with machines that automatically analyze, decide, and act.

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Artificial Intelligence and DaaS

Calling a Spade a Spade: Artificial Intelligence Terminology Discrepancies

Jan 13,2016 / By / No Comment
AI terminology

As the market for intelligent applications and the software platforms used to build them has emerged, nomenclature confusion has grown. What should we call these applications, and what should we call the platforms, libraries and software tools used to build them?

The terminology matters. Vendors need to differentiate their products from the business intelligence and predictive analytics software that has existed for decades. ‘Intelligent applications’ and ‘business intelligence’ software provide two very different sets of functionality. For technology buyers who need to justify new solutions to budget holders, the terminology matters too.

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