The day is not far off when every company will integrate features of Artificial Intelligence and Deep Learning to its processes, there is no doubt about it.
The question is: where is your business today? Are you ready?
Technology now provides us with virtual assistance, it allows us to generate ideas and analyze unstructured data – allowing entrepreneurs to focus on growing their business. Bu that’s already yesterday!
Impact of Artificial Intelligence in Business
And now with AI’s ability to analyze a problem faster than a human mind could, you will be sure that you will have considered all possible scenarios for a given situation.
Ultimately, all processes and activities related to communication, collaboration, customer service, security, production, management, product development, staff training & marketing will be analyzed and their results (performance) predicted; they can therefore be optimized and possibly automated. In addition, AI will be able to perform many of the tasks associated with these processes.
So, no need to fear Artificial Intelligence and Deep Learning because they will help you do your job better and faster in the next few years. And far from killing knowledge workers, Artificial Intelligence and Deep Learning will tend to free them to do what they are paid for: innovating, shaping, refining and improving the expertise of their business. Similarly, it can be safely asserted that highly complex tasks, intermittent or non-repetitive, and unpredictable will remain the prerogative of humans.
But what are we talking about?
Deep Learning*
Deep learning (also known as deep structured learning, hierarchical learning or deep machine learning) is the study of artificial neural networks and related machine learning algorithms that contain more than one hidden layer. Various deep learning architectures such as deep neural networks, convolutional deep neural networks, deep belief networks and recurrent neural networks have been applied to fields like computer vision, automatic speech recognition, natural language processing, audio recognition and bioinformatics where they have been shown to produce state-of-the-art results on various tasks. In the years 2000, this progress has sparked important private, academic and public investments, notably from GAFA (Google, Apple, Facebook, Amazon).
MIT – Google for Work 216 Survey**
“Machine learning is basically a way for a computer to find the nuggets of information that a human can’t,” explains Fausto Ibarra, director of global product management for Google Cloud Platform. “Once you have your data and train and deploy your models, the machine can go through terabytes of data and get smarter and smarter—basically train itself—and ultimately make predictions for you.”
Take navigation app Waze, for example. Waze churns through data to recommend faster routes to drivers in milliseconds, based on real-time traffic data — an impossible task using traditional manual methods.
Salesforce, for its part, has announced the integration of a new “Account-Based Marketing” service for the identification and targeting of strategic customers that will provide the context and factors that led to make such and such recommendations.
Another rumor is that a large US airline is working on an AI algorithm to offer intelligent seat selection to its clientele based on the shared affinities and interests of its immediate neighbors.
Evolution of Intelligence in organizations
So how do you prepare to welcome Artificial Intelligence and take advantage of it? Consider the evolution of intelligence in organisations, especially how we have gone from structured data to extraction of patterns and correlations in order to generate predictions on which to build strategies:
structured data – unstructured data – data models – predictions
You will be able to locate yourself by analyzing the level of intelligence that you extract from your data or if you want, the level of intelligence with which you use your data.
- Are you extracting significant metrics from your structured data?
- Do you collect and take advantage of your unstructured data?
- Have you defined a data model for the analysis?
- Do you use tools that allow you to identify correlations and make predictions from your data?
- Finally, are you able to adjust your strategies (marketing, product development, etc.) in real time in the light of predictions from your Artifical intelligence and Deep Learning tools?
It should be noted that, in the llight of anticipated benefits, industry experts predict that approximately 62% of organizations will use Artificial Intelligence and Deep Learning applications somehow by 2018.
Conclusion
If you have not yet done the exercise of evaluating the level of intelligence of your business data; It’s time to get to it!
It would also be recommended to immediately entrust a manager with identifying the Artificial Intelligence and Deep Learning tools available for your company and the opportunity to integrate them as well as to carry out a strategic competitive intelligence in this respect.
Denis Paul & Michel
** MIT & Google for Work Survey
Sources : Information Management, Fast Company, Wired, Huffington Post
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