Why talk about AI when we can talk about ascidians? | NTT DATA

Thu, 15 November 2018

Why talk about AI when we can talk about ascidians?

Ascidians (or sea squirts) are marine animals which attach to rocks as the larva metamorphoses into an adult. They spend the rest of their lives feeding themselves from the water they filter. During this process, ascidians undergo drastic physical changes in which, among other things, they reabsorb much of their nervous system. In short, the sea squirt eats its own brain when it becomes an adult and however surprising this process may seem, it makes perfect sense from an evolutionary standpoint. Keeping one’s brain when it is not required for survival is hugely inefficient in terms of energy consumption.

Now that you know a little more about sea squirts—you may be wondering what they have to do with artificial intelligence. As with other technologies, in their adoption process many companies follow the reverse process. They all want to have a “brain” without defining a very clear competitive advantage in terms of what they want to achieve, or what consequences they may face (e.g., cultural, ethical, reputational and social impact). In this article we will explore what issues companies should address to convert artificial intelligence into an advantage in the medium to long term.

Artificial Intelligence and Digital Transformation

Artificial intelligence can become the “brain” of our organization. But first, we must ensure that we are at the optimal phase of our evolution as a company, allowing us to convert artificial intelligence into a competitive advantage.

  • Data: artificial intelligence cannot function without data. If we do not have adequate mechanisms to achieve, control and ensure the quality of data with which our brain will work, developing the best-ever artificial intelligence algorithm will be of no use whatsoever.
  • Process automation: if our processes are still mostly manual—or if they are not well integrated—it will be very difficult to scale the impact of artificial intelligence, truly boosting our results as a company (enhancing our relationship with customers, efficiency, etc.).
  • Cultural change: this implies that certain processes should be automated or that certain roles should drastically change their working model (augmented intelligence). Moreover, other profiles will have to be added to the organization, including data scientists, Big Data architects and Chief Data Officers. This leads us to ask whether we are truly prepared to tackle this type of cultural change.

If the answer to these three questions is yes, we have a strong evolutionary basis for developing our brain.

Organizational aspects. Impact on roles and talent

 Below we will explore the organizational and technological aspects that we should analyze to successfully launch a corporate artificial intelligence initiative.

  • Creation of multidisciplinary teams for implementing artificial intelligence. Many of the profiles associated with AI are scarce (for example, Data Scientists, DataOps architects), but creating these teams with the necessary profiles is key to scale AI implementations across all areas of the organization.
  • We should invest in the necessary training and cultural change to minimize the impact of artificial intelligence initiatives on talent, refocusing roles and positions towards value-added tasks that require a strong human component.
  • Redesigning the people management model to align with the training and automation strategy linked to artificial intelligence. The incentives and career model, as well as recognition of the work accomplished, must be aligned with these new objectives and must strengthen the training component.

Technological aspects to keep in mind

From a technological point of view, there are a number of specific initiatives that should be addressed by any organization committed to the implementation of artificial intelligence in their processes:

  • Design architectures to integrate and scale AI solutions that will continue to evolve over the next few years, until they become de facto market standards.
  • Analyze cloud automation solutions and study how they fit into our strategy. Modern-day digital giants have succeeded in democratizing access to artificial intelligence solutions offering a pay-per-use format. Although cloud services can greatly accelerate the adoption of AI, they won’t deliver a competitive advantage, so it is important to consider solutions tailored to our core business processes.
  • Working on a DataOps/ProcessOps strategy. Think about how DevOps strategies can contribute to AI scaling cycles in the organization. Consider what tasks and processes can be automated, how to generate reusable assets (e.g., generic algorithms, intelligent sub-processes for common backoffice tasks).

In short, we are on the threshold of an Artificial Intelligence revolution—actual scientific results and direct business applications—but also a certain organizational immaturity for its adoption. Returning to the theory of evolution, our survival as an organization will depend largely on how we prepare our organism and capabilities (technological and human) to properly feed this new brain so it becomes a competitive advantage.

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