Identifying the ambitions of AI

AI has really expanded our horizons on the possibilities and potential that tech holds in literally every aspect of our lives – the limits of which are continually changing. 5G has had an immediate impact on unlocking the creativity & innovation behind the "smart" solutions available today, with no sign of slowing down. Can AI tackle real-world problems in today's workforce? Skeptics often fault AI and tech for job losses, among a slew of other allegations - but, in truth, when automated processes can often eliminate a company's need for more staff. That need not be the case moving forward.
 
Having said that, the infrastructure is in place - with a roadmap of upgrades to come - the policies have to yet be written, and sectors like employment, healthcare, and communication are poised to benefit greatly from AI-driven automation. But what does that mean for more manual laborers who lack access to the network? The ambition of connecting people is at the core of the telecoms sector. The shifting culture within the industry to enable more remote communities has been enabled through network innovation plenty over the last decade. Network enterprises are the seeds of change. 

The TM Forum recently launched the Inclusion and Diversity Score (IDS) – the world’s first comprehensive score improving company and industry-wide diversity and inclusion. Co-created and piloted by TMF members, this facilitates digital service enterprises to “win the war on talent” by improving, maintaining, and nurturing talent and organizational culture. Aside from providing multidimensional benchmark-ready scoring – a single metric measuring a company’s standing using machine learning (ML) – measuring and reporting an enterprise’s leadership compared with an organization's internal demographics based on age, gender, ethnicity, racial diversity, as well as LGBTQ+. The 15 pilots launched have yielded some favorable results in the data collected and prove promising for wider adoption and the socioeconomic and geopolitical impacts it will carry in the real world. 

While this is a use case of a positive impact on the workforce – can this solution solve more inclusive hiring modes for the workforce in areas that are not as connected? There are socioeconomic, geopolitical, and cultural barriers to overcome, but it serves to the benefit of service providers to identify those sensitivities for those communities. Price points for bundles, data, and devices; sufficient coverage strength, and tackling potential insufficiencies in the skills of locals through training programs can have resounding effects on proliferated use of the network. While these would be managed by people more so than AI, it is worth highlighting that AI can solve most problems and not all. And, the relationship between humans and AI is mutually beneficial. 

Using IDS as a steppingstone toward further automation to empower those lower coverage areas enables another dimension of inclusivity in the workforce. Post-pandemic norms of working from home and hybrid working habits have allowed a wider range of people to be more self-sufficient and more connected to the grid with the devices used for their jobs. This is a classic example of how incentive-driven connectivity can promote wider coverage based on local needs.