Artificial Intelligence (AI) continues to be the buzzword du jour. However, is all the hype and marketing promises based on reality? As we’ve learned from the past, simply adopting new technology doesn’t always resolve organisational issues. In fact, sometimes the ‘technological fix’ can result in monetary loss.
Reaping the benefits of advanced technologies such as AI, requires telcos to
1) have a deep understanding of the issues the business is trying to resolve,
2) have clearly defined metrics of what constitutes success,
3) align the technology with the operator’s short- and long-term business goals.
Before taking the AI leap
PwC’s Global Artificial Intelligence Study: Exploiting the AI Revolution estimates AI investments will have a global economic impact of $15.7 trillion by 2030. However, for all practical purposes this technology is still in the early stages of development, and while telcos are moving forward with AI initiatives, due diligence is recommended.
Taking lessons learnt from past technology implementations is a good place to start before making considerable AI investments. For example, not too long-ago big data and the potential value of large data sets were dominating headlines and conversations. While vendors were pushing big data strategies, their actual goal was to sell Hadoop-based or proprietary storage solutions. For these vendors, the value of big data was secondary to the technology.
Pinning their hopes on the value promised, many operators invested heavily in big data, only to learn costly lessons. Lessons learned then are just as applicable today: Technology doesn’t automatically equate to value.
Navigating the AI promise
From automating repetitive tasks and improving efficiency and productivity to making better decisions and enhancing the customer experience, AI vendors are promoting the unlimited potential this technology can provide. While AI promises great value, due diligence is required before making the investment.
Given the varied challenges operators face, as well as the industry’s inherent complexities, AI value can’t be expected out of the box. Operators need to pause and do a reality check that starts with the training AI will require to understand the business, its processes, data and technologies. However, there are functions where AI can add almost immediate value, such as automating tedious or repetitive tasks, analysing extensive data sets, handling predictive analytics, personalising recommendations and delivering support. This reality check is essential for operators to recognise AI’s current limitations, including:
- Making complex decisions: Without human understanding and emotional intelligence, AI lacks the ability to handle complex decision-making scenarios. This is especially true for decisions that involve ethical considerations or an understanding of human emotions and social norms.
- Thinking abstractly or creatively: While AI can process data and support innovation, creativity remains a human trait.
- Developing relationships: AI doesn’t have the capability to develop or maintain meaningful client, partner, or other stakeholder relationships.
- Formulating strategies: Developing strategies requires a deep understanding of many complex factors such as human behaviour, as well as social and economic, which AI may not fully comprehend.
- Understanding and interpreting context: AI can struggle with understanding and interpreting nuanced human communication and context, which can be crucial in negotiations, conflict resolution, or other sensitive business areas.
Although all industries face obstacles when it comes to implementing AI, the telecom sector faces unique challenges.
Realise the potential: The way forward with AI
While AI use cases appear endless, especially with the recent rise of ChatGPT, history provides cautionary tales to validate marketing promises. Whether you’re relying on AI to help grow revenue, improve the customer experience, reduce costs, boost operational efficiency, or automate processes, technology history and experience cautions that the marketing hype may be different than reality. When making the decision whether to invest in AI or not, telco’s need to ask AI vendors difficult questions, such as:
- How does the vendor validate claims made about their AI’s capabilities?
- What inputs are required to gain maximum return on investment (ROI) from the AI solution?
- How does the AI vendor define and measure their AI’s success for the specific and unique requirements of a telco environment?
- Can the vendor provide and justify an ROI timeframe?
- Given how rapidly AI is changing, how is their AI solution positioned to evolve?
The responses to these questions will help operators in deciding whether AI will help to resolve their challenges, provide solid information on how to gauge the success of the AI investment, and determine if the technology is in alignment with the operator’s business goals.
In addition to the answers provided by the AI vendor, telcos should prioritise their objectives using methods like the MoSCoW Prioritisation Technique (MoSCoW Analysis), the RICE (Reach, Impact, Confidence and Effort), or the Kano model. Leveraging this information will help the telco determine if onboarding AI is the right decision for their needs.
MoSCoW (Must Have, Should Have, Could Have and Won’t Have) prioritises the telco’s need for technology in each of the four categories and focuses on what matters most to both the customer and stakeholders. For example, suppose the AI component of a vendor’s offering falls outside of the operator’s list of Must Haves or Should Haves. This sends a clear message that the value of that AI solution has, at best, not been verified or is dubious.
To realise AI’s true potential, telcos must ask vendors the hard questions and prioritise objectives. The journey from potential to actual AI value relies on a comprehensive understanding of the problem(s) the operator is trying to resolve, awareness of what constitutes success and a relentless focus on aligning AI deployment with solid business objectives.
Operators that are on the verge of investing in AI need to ensure that their strategy is rooted in discernment, perform due diligence and be persistent in the pursuit of tangible AI value. AI can be the answer to your telco’s challenges, but getting there is a voyage that requires careful navigation and persistency in separating marketing hype from tangible value.
Article by Brian Murray, the head of product marketing at Anritsu
About Brian Murray
Brian Murray is the head of product marketing at Anritsu Service Assurance. He has over 12 years’ experience in the telecom industry and has worked for some very recognisable companies such as The NOW Factory, IBM and Mobileum, where his many roles spanned both product and marketing. His passion lies in creatively communicating the real value of his product suite to customers while matching it with their needs through a deep understanding of their unique pain points. His dedication to this philosophy has been instrumental in building lasting relationships with customers and positioning Anritsu Service Assurance as a leader in its domain.
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