You may be aware of the famous Move 37 in the Go game when AlphaGo, an artificially intelligent computing system built by researchers at Google defeated Lee Sedol, one of the world's top players in March, 2016. The game took a dramatic turn when AlphaGo instructed its human assistant to place a black stone in a largely open area on the right-hand side of the 19-by-19 grid of the game. The potential legal board positions in Go are greater than the number of atoms in the universe. This was the first program to beat a professional at the most complex game mankind ever devised.
Artificial intelligence has been making headlines more in the consumer realm but not in the enterprise. According to Forrester, the key reasons why many enterprises haven’t adopted Artificial intelligence is they hadn’t come to terms with how to use it, the skills gap in their organizations and the infrastructure not being ready.
Some enterprise early adopters are reporting promising results. Cisco Stealthwatch provides network visibility and security analytics. Cisco Stealthwatch uses an AI powered NetFlow to provide visibility across the network, data center, branch offices, and cloud. Its advanced security analytics uncover stealthy attacks on the extended network. Stealthwatch makes use of the existing network as a security sensor and enforcer to dramatically improve your threat defense.
Microsoft’s use of AI now goes beyond its Bing search engine and now includes its Azure cloud computing service, which puts the company’s AI tools in the hands of Azure customers.
As more firms digitally transform and seek competitive advantage, they are looking to Artificial Intelligence for answers. Being an AI-first enterprise means an organization incorporates A.I in most business processes and software solutions in the organization. The A.I-first business transforms data into intelligence to improve internal processes and outcomes.
How does an enterprise get started and win in Artificial Intelligence?
When getting started and keeping in mind with the emerging nature of the technology, we recommend assembling AI task force, to avoid duplicating technical efforts, maximize the collective talent and creating a company-wide strategy. This approach is helpful especially for in-house development. The advantage of building an A.I team is that it will lead faster to aggregation of data into real value. This team has to be drawn across all business units in the enterprise. The team may have A.I technical skills or not.
The task force will be tasked with prioritizing projects, collecting the learnings and gradually create best practices that will become part of the AI development DNA of the company.
When getting started, it is advisable to start implementation with one business unit in the enterprise that can deliver quick and visible wins. For the start, let’s consider AI in the IT business unit. AI is good at learning millions of parameters to solve a specific task. In the IT business unit, we can find the most parameters in back-end management, for instance reducing inefficiencies through automation and optimization.
After the business unit has been identified, the potential of AI needs to be validated, brought into production and used. Set up small internal teams of developers. It is advisable to use early Proof of Concept solutions using open source frameworks and open datasets.
Amazon has made it easy for developers of all skill levels to use machine learning technology by providing visualization tools and wizards that guide you through the process of creating machine learning (ML) models without having to learn complex ML algorithms and technology. Once your models are ready, Amazon Machine Learning makes it easy to obtain predictions for your application using simple APIs, without having to implement custom prediction generation code, or manage any infrastructure.
After successfully testing one business unit, move on to another business unit and eventually cover the entire enterprise, where AI can have a big impact.
AI has the power of transforming enterprise ideas into products and services relevant to the business with relatively low people and infrastructure costs. This underscores why more enterprises are looking forward to Artificial intelligence, to solve some of the world’s most challenging problems.