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Biz Plan Competition | Alive

Total Raised

$10K

Last Raised

$10K | 2 yrs ago

About Sustainable AI

Sustainable AI is an organization that provides accurate forest inventory to aid reforestation efforts.

Sustainable AI Headquarter Location

Peru

Latest Sustainable AI News

4 Essential Steps for a Sustainable AI Rollout in Your Organization

Mar 15, 2018

Artificial Intelligence is emerging as a very important technology for business – but is business ready for AI? Gabby Menachem, CEO, Loom Systems, discusses some methods that organizations can use to ensure as painless a rollout of AI as possible. Artificial Intelligence (AI) is, without doubt, a growing business trend. In fact, According to Gartner , by 2021, 40% of enterprise applications offered by service providers will incorporate AI. Once seen as a novelty to impress customers, AI-based machines, robots and data systems are operating as concierges in hotels, making financial decisions in banks, offloading fatigue-inducing maintenance functions of IT personnel, and so much more. And, as that old song goes , we ain't seen nothing yet. Down to business: How it’s actually done Implementing AI, like anything else, requires multiple resources and, in many organizations, funds are not the only cost involved . There are many adaptations required, internally, when implementing AI - integrating AI into the daily routine of employees who are used to performing many tasks manually, and dealing with the reluctance some managers might have in offloading responsibilities to a machine or database, are just the beginning of an internal sync required to set the proper grounds for AI absorption within the organization. The shock of the new 1. What are we doing here, anyway? That's a question many employees will be asking when AI systems are implemented and if top management wants to introduce AI to its workers, they need to come prepared with the answers . For that to happen, they will need to discuss the AI benefits, as well as introduce a roadmap with the entire AI adoption process, including organizational and departmental KPIs and bottom lines they expect to be improved. In many companies, the lack of such a plan results in AI adoption failure, as managers with a budget buy into the “flavor of the month,” with systems languishing from underuse because there was no plan to integrate them into the regular workflow. The benefits of AI are too great, and the incorporation of artificial intelligence too important, to allow that to happen. 2. Follow the leader A most helpful idea is appointing one company official (or even a new hire) as the “AI Evangelist,” who will be in charge of helping to develop, implement and supervise the AI rollout. Part of advocacy is convincing others in the organization that the AI project is important and needed – not a threat, not an annoyance, and not a burden . Along with firm guidance that AI is an integral strategy in the organization, and that everyone is expected to do their part, the AI evangelist needs to provide the vision of just how AI can help the organization - how AI will make work easier, save the company money, and enable the company to grow. And, when the company grows, it doesn't fire people – it hires them. Hopefully, with an organized program that advocates for the use of AI, shows off the benefits of the system, and works to promote its use in the organization, many more people in the company will become advocates of the system as well. With this notion coming from senior management, appointing such a change agent can make the difference between a fail and a win. 3. All aboard! AI needs the masses 4. AI needs experts Sometimes, the desire to implement AI in an organization fails due to an inherent paradox: on one hand, the organization is very much interested in adopting AI, which will assist the company to overcome the skill gap , however, on the other hand, 54% of companies trying to adopt AI admit that they lack skilled workers . The irony is clear: while a company acknowledges that the very use of AI methodologies can help with understaffed departments, it cannot afford itself to release the same individuals performing daily IT tasks to courses and conferences to learn new AI skills. This is where data scientists can help, by bridging a knowledge gap and providing the essential know-how and guidance through the AI adoption process . Tags

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