Artificial intelligence (AI) has had a tremendous few years. It was not all that long ago that AI was not ready for mass use, yet now we can scarcely imagine living in a world without tools like ChatGPT and so on.
For telcos, things like deep learning (DL), machine learning (ML), and natural language processing (NLP) hold exciting new possibilities, especially as growing 5G availability is set to increase consumer demands. However, doing that rests on scalability, flexibility, and simplification of people, processes, and technology.
The debate isn’t so much if AI will reshape society - because it already is - but how telcos can utilise it to maximise the best outcomes. Despite research noting a healthy appetite for investment and research & development, there are no certainties of guaranteed AI readiness.
Challenges to human-centric AI
Perhaps because of AI's immense capabilities, there is also a fair share of undue hype. That's why it is crucial that telcos do not just think about adopting the newest tools. Instead, the focus should be on strategic capability building.
According to IDC, 65% of CIOs face pressure to adopt digital tech, such as generative AI and deep analytics, but limited IT support will diminish the benefits and heighten risks. The seemingly perennial talent gap emphasises the importance of nurturing AI skills.
Although upskilling and reskilling is critical, low-code tools are equally important for empowering a broader spectrum of professionals to actively participate in AI-driven transformation.
Meanwhile, in the face of public policy frameworks aimed at implementing guardrails for AI development, striking a balance is key. Unbridled AI use is bound to fail to account for the impact on our communities. Telcos can, however, leverage partners and experts who have been at the forefront of AI integration to develop a clear-headed strategy.
A robust ecosystem via intelligent strategy
Establishing a robust data ecosystem at the offset is crucial to leveraging AI to propel businesses to new heights of speed and precision. Telcos will need to be able to take stock of the following:
Data accuracy - It's been said countless times, but it bears repeating that AI is only as good as the data at its disposal. An intelligent strategy will enable businesses to aggregate data from disparate sources into a single source of truth. The right approach will resolve discrepancies, standardise data definitions, and provide ongoing assurance of high data quality.
Data completeness - Businesses must also be able to determine whether data sets are sufficiently complete. Newer sample sizes can generate less accurate AI output versus comparatively older data sets. This hampers predictive analytics, compliance, and even exacerbates biases.
Process integrity - Process workflows also need to be logical and seamless if AI is to drive automation. While models can suggest optimal workflows, it’s still up to leaders to test sequences and try to “break” a workflow with an unexpected condition. Due diligence upfront will minimize the risk of a process disruption that leaves stakeholders stranded.
Trust and security - Securing sensitive data, including personally identifiable information (PII), is vital to building trust among stakeholders, both internal and external - especially your customers. Look to ensure data access only to authorised systems and individuals, and implement a data governance framework that strengthens accountability and compliance with company and regulatory standards.
Achieving AI-readiness
Becoming AI-ready is systemic. People are as crucial to this as technology is - with the transformation requiring skilled personnel who can harness AI insights and apply them effectively. Telcos stand to gain immensely from cultivating a culture of curiosity, openness, and learning - with strong partners and vendors providing support. Processes must be mapped, evaluated, and automated where possible while respecting ethical considerations and maintaining robust data governance. That requires an IT infrastructure equipped for handling data at the right time, in the right form, and in a secure manner.
Ultimately, success in the AI era hinges on clear goals, comprehensive documentation, accountable stakeholders, prioritisation, and a high level of automation. For many organisations, this is a substantial shift in mindset. But with the right technologies and highly effective support, telcos can achieve the necessary agility to learn and adapt continuously.
