AI represents a game changer for the telco industry. Although first movers have already embraced AI, separating hype from opportunity remains challenging. Becoming an AI-amplified telco calls for more than being fascinated by the technology’s potential and piloting use cases. This Viewpoint focuses on the necessary building blocks to exploit AI’s 5%-7% EBITDA potential and outlines how to achieve lasting success by analyzing the full picture, including technology, AI governance, and culture.

One of the front-row candidates for disruption by artificial intelligence (AI) is software product and service development. AI is already leading to a paradigm shift in aspects such as coding, architecture, security, service management and ticketing, and personalization, providing new opportunities and risks. But the implications go well beyond new products and services and improved development approaches, into how software enterprises need to transform themselves across the board, from strategy and organization through to capabilities, resources, and ways of working.

In a data-driven world, product manufacturers have a stark choice – either digitize to become more flexible and customer-centric or be sidelined by nimbler competitors. They need to embrace the transformative opportunities that data and the Internet of Things bring to add value to their offerings and change their business models. All businesses understand the vital importance of collecting, analyzing, and acting on data to enable: New business models, such as offering as-a-service or outcome-based pricing, and entering the Industrial Metaverse

How decarbonization, decentralization, and digitalization transform the energy and resources sector

Big Data can deliver the promise of converting data into competitive advantage

Being capable to react to change with agility is a key requirement for all companies onboarding digital business models or digital products and processes. It is becoming even more of a necessity to compete. Yet large and grown companies, in particular, see many challenges with the necessary balance between agility and stability – implementing agile methodologies outside the technical domain fails in many cases for many reasons.