Automation And AI: How To Make The Most Of Your Data

Once the stuff of science fiction, automation and artificial intelligence (AI) are all around us today. AI in particular has a growing presence in our lives, including AI-powered assistants on retail websites, AI-supported fraud prevention, viewing recommendations on Netflix, and autonomous vehicles. Even the rapid development of mRNA vaccines has cast a spotlight on the transformative potential of AI in healthcare.

In the business world, automation and AI have countless applications. Considering the mountains of data generated by the rapid adoption of digital tools during the volatility of the COVID-19 pandemic, executives should be considering whether and how automation and AI might benefit their business.

Get smart about data

Automation and AI are obsolete without data, so as the use of these tools have grown, the imperative to capture and mine data sets has expanded dramatically as well. Business leaders are making a renewed commitment to good data hygiene to facilitate sharing and transforming data companywide. Trustworthy data can be analyzed for patterns that can provide worthwhile insights.

Many companies have accumulated disparate streams of data across various departments and divisions. Executives need to look across silos, thinking broadly about all of the data streams they have access to and how those might be incorporated into AI and automation initiatives. These disparate data streams might also be housed within different legacy systems, so leaders also need to explore opportunities to update and consolidate systems.

Going through the exercise of cataloging data streams and systems can help leaders see where data lives, how much can live together, and the data security concerns to be aware of. If a company is managing huge data sets with poor data hygiene or clunky systems that can’t communicate with each other, they will struggle to pursue the free sharing and transformation of data.

Read more

Mots-clés : cybersécurité, sécurité informatique, protection des données, menaces cybernétiques, veille cyber, analyse de vulnérabilités, sécurité des réseaux, cyberattaques, conformité RGPD, NIS2, DORA, PCIDSS, DEVSECOPS, eSANTE, intelligence artificielle, IA en cybersécurité, apprentissage automatique, deep learning, algorithmes de sécurité, détection des anomalies, systèmes intelligents, automatisation de la sécurité, IA pour la prévention des cyberattaques.