Once adopted, Enterprise AI strategies, require enforcing data governance where each collaborator has a role and contributes to data enrichment, processing, and security.
If we are to benefit from all Artificial Intelligence (AI) advantages such as optimizing processes, improving the relations with customers and providers, innovation, anticipating events, predictive maintenance and supporting collaborators in their endeavors, AI must be thought through in a coherent and comprehensive way at a company level. This Enterprise AI approach requires uptake by all collaborators and the roll-out of a company artificial intelligence.
AI started making appearances in our world with robots on assembly lines, predictive tools in maintenance, chatbots for marketing or HR departments, and facial recognition for security services. Over time, it has spread to all business unit management. This intrusion happened through technology and it was mostly small teams that conducted roll-outs in an isolated way.
Therefore, businesses and especially key accounts are now the proud owners of numerous independent applications that are spread out through departments, without any real orchestration or effort to capitalize on them. Such an approach with no governance for AI projects might have been justifiable in the past because we were not certain that these applications were worth it yet, but it is no longer the case as the benefits of these new technologies have now been demonstrated.
It is now time for businesses to set up comprehensive artificial intelligence strategies and move on to the Enterprise AI era where automation is seen as a crucial facilitating factor for each business process.
Enterprise AI Requires Uptake by All Collaborators
Moving on to the Enterprise AI era requires global uptake by the company. By mobilizing collaborators, executive management must be the driving force of this process and receive support from managers and ambassadors. Implementing Enterprise AI needs explaining, reassuring, demonstrating through tangible projects that AI is a support tool, a tasks facilitator, and not a replacement. It requires from collaborators that they think about how AI can assist them in their daily work.
- Which time-consuming activities and tasks can they entrust artificial intelligence with?
- What new AI-based services can they offer to their clients?
- What applications can be implemented to optimize their processes and anticipate events?
Any AI project must be approached as a strategic business challenge and not just as a technology element; a global AI strategy even more so. Demonstrating the added value of an AI and analytics application is the best way to leverage collaborator energy and multiply their initiatives.
No Enterprise AI Without Data Culture
All artificial intelligence projects require large volumes of data. Therefore, Enterprise AI must instill data culture in all its collaborators. Education, training, workshops and working groups, all means must be used in order to bring everyone to engage in a data-oriented behavior. However, in order to still be able to control the entire structure (so that AI can be regarded as capital when calculating the company’s value), creation, test design and production launch processes also need to be thought out with utmost care to avoid the type of excesses, mistakes and incidents that were recorded over the past few months.
Once adopted, Enterprise AI strategies, therefore, require enforcing data governance where each collaborator has a role and contributes to data enrichment, processing, and security.
Whether in clients relations, logistics, design, production, maintenance, sales, human resources or purchases… AI is spreading to all business units of companies. However, artificial intelligence will only develop its full potential and enable companies to create new products, new business, to rationalize costs and boost reactivity if it is rolled out a company level. The time for dithering is over; AI has proven itself. All companies must now join the Enterprise AI era.
Companies that want to be more efficient or develop new products in the coming years will need to adopt Enterprise AI to make it happen. And while the year 2018 was supposed to be a banner one for AI in the enterprise, more and more, companies are finding that it is much easier talked about than executed.