Many vendors are indiscriminately applying the artificial intelligence (AI) label (“AI washing”), and a lack of differentiation is “confusing buyers”, according to analysts at IT research company Gartner. The company found 1,000+ vendors with applications and platforms describing themselves as AI vendors.
The widespread use of “AI washing” is already having real consequences for investment in the technology. To build trust with end-user organizations, vendors should:
- Focus on building a collection of case studies with quantifiable results achieved using AI.
- Use the term ‘AI’ wisely in sales and marketing materials, and be clear what differentiates their AI offering and what problem it solves.
The main AI challenge is not enough skilled staff according to over half of respondents (IT business leaders) of Gartner’s 2017 AI development strategies survey. Organisations are seeking AI solutions to improve decision making and process automation, and faced with a choice, most would prefer to buy embedded or packaged AI solutions rather than trying to build a custom one. This is a prime opportunity for vendors to take advantage by:
- offering solutions to business problems rather than just cutting-edge technology;
- highlight how your AI solution helps address the skills shortage; and
- emphasize how it can deliver value faster than trying to build a customer AI solution in house.
Less complex machine-learning
AI advancements like deep learning are getting a lot of buzz but are obscuring the value of more straightforward, proven approaches. Vendors should use the simplest approach that can do the job over cutting-edge AI techniques.
Rise of the machines
It doesn’t surprise that vendors have gotten caught up in the AI gold rush. Gartner found that at the beginning of 2016, the term “artificial intelligence” was not even in the top 100 search terms on its site. By May 2017, the term ranked at number seven. The company ever predicted that by 2020, AI technologies will be in almost every new software product.
“AI offers exciting possibilities, but unfortunately, most vendors are focused on the goal of simply building and marketing an AI-based product rather than first identifying needs, potential uses and the business value to customers,” said Jim Hare, Research Vice President, Gartner.
Data analytics and AI: Key to end-to-end management
Many businesses are adopting business process automation, network functions virtualization (NFV), software-defined networking (SDN), cloud-based applications and, in the case of mobile operators, 5G technology to meet the seemingly insatiable demand for connectivity and new applications.
Read this TM Forum report to understand:
- how and why network and service management must evolve;
- the role for orchestration and closed control loops;
- how operators are using analytics and machine learning;
- obstacles operators must overcome;
- why 5G is particularly challenging – but also promising; and
- how TM Forum’s Catalyst program is helping operators address the challenges.