The Information and Communication Technologies (ICT) industry in Portugal is at a significant inflection point, driven mainly by the rise of Generative Artificial Intelligence (AI). This new technological paradigm has captured global attention, not only for its disruptive capacity, but also for its rapid growth and adoption. Indeed, the impact of Generative AI on the domestic market promises to transform not only company operations, but also business models and our entire economy.

But Generative AI has not emerged from a vacuum, it is the result of a decade of substantial investment in various emerging technologies. This evolution is largely supported by the third technology platform, which includes technologies such as cloud computing, social media, and mobile devices. These innovations have enabled an explosion of new data both structured and unstructured, creating fertile ground for the advancement of AI.

With organisations transforming into digital business, the result has been a huge amount of new digital data: structured, semi-structured, and unstructured. Take, for example, the volume of new data generated by the biotech industry as innovative electronic health records and DNA sequencing emerged. In all economic sectors we see a similar digital trajectory, where data will be at the disposal of Generative AI to augment work and simplify operations.

It is in this context that the rapid adoption of Generative AI is moving AI from an "embryonic" software element to a core technology at the heart of organisations. We believe that the adoption of Generative AI will deliver the same (if not better) kinds of gains that we saw in the digital pioneers (four times revenue growth and five times profitability), and this will happen at an accelerated rate. And to stay competitive, all business leaders will need to develop an AI strategy to address the key use cases, use policy, intellectual property, data inclusion, costs, security, and implementation of Generative AI.

But how can Generative AI create value for my organisation?

From IDC's perspective, the impact of Generative AI is enormous, but it requires the prioritization of an identified set of use cases, i.e. a business-funded initiative, supported by technology that delivers a measurable result. And in this context we can define three types of Generative AI Use Cases that need to be evaluated according to their impact in the short, medium, and long term.

Short-term impact: Generative AI use cases to increase productivity

The Use Cases for increasing productivity will have the most impact in the short term. They are aligned with current work tasks, such as summarizing a report, generating a job description or generating software code. These productivity-enhancing features are already being incorporated into existing productivity applications and are already being used by more than 50% of companies - including concerted actions in the organization or just individual use by an employee.

Medium-term impact: Generative AI Use Cases for a Function

Business function use cases will have even more impact than productivity use cases, but from a more medium-term perspective, because they tend to integrate a model (or several models) with corporate data for the transformation of an entire department or specific function (marketing, sales, procurement, etc.). Many organizations are testing these types of use cases but are concerned about the risk in terms of intellectual property and data governance. These business function use cases require integration with established business applications and platforms from ERP vendors, RPA, etc.

Long-term Impact: Generative AI Use Cases for an Industry

Industry use cases will be the most disruptive, but the impact will be more long-term because they require more customized work (and in some cases may even require building generative AI models of their own). Examples include the discovery of generative drugs in the health sector, the design of generative materials for industry, the development of new forms of energy management and transmission, etc. And it has the potential to create major disruptions and be a source of real business value creation for large companies that are able to gather, individually or with their ecosystem, a sufficiently large set of data and train it and enhance the discovery of new products and services.  

In this context of rapid evolution and technological disruption, it is essential that business leaders adopt a culture of continuous learning and develop digital skills in their organisations, as well as regularly develop and update their digital transformation strategies and roadmaps, or if they have already incorporated digital into their business, update their business strategies taking into account the impact of Generative AI.

Do you know the program
Applied Digital Transformation: from thought to action?
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