Data-Driven Business Architecture – Executive Guide Artificial Intelligence (AI)

The journey to artificial intelligence (AI) and data-driven business architecture.

In today’s era of big data, Artificial Intelligence (AI) and cognitive technologies are becoming a powerful focal point for businesses. They are increasingly being used to intelligently automate and accelerate business processes, make valid predictions, create more engaging and personalized customer interactions, and ultimately recommend the best possible approach to assess a business problem. And in doing so, create an enterprise that is data-centric, agile, and future-focused: the Cognitive Enterprise.

Artificial Intelligence (AI) is a term that has been circulating through the media and companies for some time now as a panacea on the one hand and as a specter on the other.

While more and more companies are building up their own AI expertise and adopting AI systems in productive operation, other companies continue to ask themselves what added value artificial intelligence brings with it or whether it is just “hype” that can be set out.

The series of articles entitled “The Executive Guide to Artificial Intelligence” is intended to shed light on the subject from various angles and provide clarity. In the first part, we first address the general question of why a data-centric corporate strategy will be so important for the digital transformation of a company in the future and what contribution artificial intelligence will make to this.

Digitization empowers customer-centric thinking

Businesses face an unprecedented interweaving of technological, social, and regulatory forces. Ongoing digitization as well as Artificial Intelligence (AI), automation, Internet of Things, Blockchain, and 5G are pervasive, changing standard business architectures. Since 2000, 52% of Fortune 500 companies have either gone bankrupt, been acquired, or been dissolved.

But it would be wrong to name digitization and technologies like AI solely as disruptors, because:

  • Netflix didn’t destroy video rental giant Blockbuster, but ridiculous late-night movie rental fees.
  • Uber didn’t destroy the cab business, but limited accessibility and fare control.
  • Apple didn’t destroy the music industry, forcing people to buy full-length albums did.
  • Airbnb didn’t destroy the hotel industry, limited availability and pricing did.

These four examples quickly make it clear that countless industries are changing right now. But they also show that digitization and technology, including AI, are not only disruptors but also enablers that can be used to make products and services even more customer-centric.

The digital transformation of companies is changing

The development of digitization is a very exciting one: For the last ten years, the digital transformation of companies has been driven “outside-in.” That is, external factors such as changing customer expectations and extensive interconnectivity have been key drivers of digitization. Today, digitization development is giving way to the “inside-out” potential of data, which uses exponential technologies such as artificial intelligence, blockchain, and the Internet of Things (IoT) to harness data for the enterprise.

According to Gartner, the amount of enterprise data generated will increase by 800 percent by 2020. That’s a huge amount, and it’s also available in different formats and stored in different places. The winner today is the one who …

  • can make the most of the data and thus offer the best and most individualized products and services, and
  • use this data and build value-added business platforms.

Artificial intelligence is essential for effective data processing

To implement these processes, the capabilities of exponential technologies are needed. In this context, the use of artificial intelligence is also becoming increasingly important. This is because around 80% of corporate data is unstructured, such as emails, videos, PDF files, or paper documents. By recognizing patterns in data, AI algorithms make it possible for the first time for a machine to process unstructured data in context and continuously learn from new data, feedback, or interactions.

AI algorithms enable machines to mimic intelligent human behavior and process data in ways that previously required laborious programming by rule-based systems.

The next-generation AI-enabled business model is the Cognitive Enterprise

Companies can already productively use AI to intelligently automate and accelerate business processes, make valid predictions, create more engaging and personalized customer interactions or even new products, and ultimately recommend the best possible approach to evaluate a business problem. However, to effectively use AI systems, integrate diverse data, scale, and combine with other technologies, companies would need to think holistically and should align their long-term business strategy in terms of a “Cognitive Enterprise”, the establishment of a data-driven business model. The vision of an AI-infused enterprise primarily includes the following seven components:

  • Build internal and/or external business platforms that leverage deep expertise, open workflows, and data synergies via AI to unlock expansion potential within an ecosystem.
  • Combine proprietary and heterogeneous data through enterprise-wide data integration to create deep context and insight.
  • Build enterprise structure and architecture that enables agility and flexibility, and is ready not only for today’s technologies and AI infrastructures but also for future technology advancements.
  • Rethink strategic business processes and workflows and humanize and automate them from start to finish using AI. AI systems can redesign workflows by orchestrating interactions between intelligent machines and even smarter humans.
  • Actively integrate agility into company culture and processes to be able to change quickly, realign, and build new things. AI systems do not work in a linear approach (waterfall model).
  • Actively develop and hire employees based on curiosity, aptitude, and ability rather than specific technical or professional skills.
  • Find a healthy safety balance by limiting excessive caution but ensuring necessary safety.

The use of artificial intelligence requires a permanent change

The transformation to a Cognitive Enterprise and also the development of comprehensive AI systems is not a task that can be completed overnight, just as the process of “digitization” will never be complete.

The first companies from various industries are already exploiting the potential of AI technology and are well on their way to becoming a Cognitive Enterprise.

Today’s businesses are undergoing a permanent change that is continuously accelerating. But as always in history, the winners will be the companies and people that adapt best and fastest to these changes.

In the second part of the series “The Executive Guide to Artificial Intelligence”, I will go into more detail on how to identify and implement applications for AI in your organization.

Britta Daffner ist seit über einem Jahrzehnt in der Technologie- und Daten-Industrie zu Hause. Ihr Credo: Innovation und Digitalisierung von Unternehmen vorantreiben – durch Technologie und Führung. Dafür befähigt sie als Abteilungsleiterin im Bereich „Artificial Intelligence & Data Science“ in der Beratungssparte von IBM Unternehmen dabei, das volle Potential aus Daten zu nutzen. Daneben ist sie Autorin des Buches "Die Disruptions-DNA, sowie Coach und Mentor von Leadern, die in der Konzern- und Wirtschaftswelt etwas verändern wollen.

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