Will AI Replace Content Writers?
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The telecommunications industry has been thirsty for growth for over a decade. Revenues have stagnated amidst rising costs and intensified competition, and most operators have struggled to innovate. But emerging generative AI capabilities may offer telcos the answer they’ve been waiting for - if they choose to embrace it.
Early results from companies piloting these technologies suggest generative AI could ignite transformational improvements in customer experience, operational efficiency, product development, and beyond. One European telco increased marketing campaign conversion rates by 40% while cutting costs via AI-enabled personalisation. A Latin American operator boosted call centre productivity by 25% and improved customer satisfaction by enhancing agent skills with generative AI recommendations.
And they achieved these results in weeks - the first use case went live in just two weeks. For an industry where execution has historically been sluggish, it shows the power of AI that learns continuously from data and interacts conversationally.
Our surveys with telco leaders confirm generative AI is already gaining traction. The vast majority are piloting solutions ranging from proofs-of-concept to full deployments. Warily optimistic about the potential, they expect domain impacts ranging from 10-40% cost savings and revenue increases in the next 2-3 years. Areas like customer service, marketing, and IT are early priorities.
But while budgets and staffing continue to grow, there is still uncertainty about whether generative AI will be genuinely transformational or just table stakes. Despite quick wins, only a third of executives said AI was an organisational priority. Grassroots advocates still struggle to justify use cases. And fundamental challenges like data quality and AI talent remain.
This reflects telcos’ crossroads as an industry - whether to embrace generative AI as the catalyst for renewal or let inertia win. Can a legacy industry known for incrementalism rather than innovation decisively break from the past?
The stakes could not be higher. As AI democratises access to insight and automation, competitive advantages may soon erode. Incumbents will face new threats from smaller rivals now on equal analytics footing. In a $100 billion market, the spoils will go to those who tap generative AI at scale first across the enterprise - what we term the “AI-native telco.”
Thankfully, transitioning to an AI-native operating model is achievable for those with proper vision and commitment. We believe in six foundational pillars:
Like any digital initiative, generative AI requires aligning leaders around strategic value, use cases, and roadmaps. But decisions around build vs. buy and open vs. proprietary approaches take on new weight. One key is creating “control towers” - centralised hubs that oversee the portfolio, promote reusability, and orchestrate enterprise-wide governance.
While less specialised than traditional AI talent, generative AI requires key capabilities like prompt engineering. More critically, it demands more subject matter experts to oversee data and model quality. Organisations must nurture internal talent through training programs, certifications, and recruitment.
With new research daily, keeping pace with innovation requires dedicated “GenAI Labs” to prototype and integrate cutting-edge tools. Widely reusable modules and self-service components will maximise the sharing of solutions. LLM Ops teams will ensure rigorous monitoring and adaptation of deployed models - similar to ITOps today.
Unlike traditional analytics, generative AI thrives on unstructured data from documents, images, and conversations. Telecoms must set up expansive pipelines - while carefully governing usage, IP, privacy and other risks. Some firms use structured reviews of every proposed use case to validate security and compliance.
As generative AI augments or automates virtually every role, sweeping reskilling/upskilling is crucial for adoption. Solutions themselves can assist in personalising training content for agents, technicians, and other users. But senior leaders must champion and fund the multi-year effort.
Finally, the successful AI-native telco nurtures a culture comfortable with iteration, experimentation, and occasional failure rather than rigid processes. Leadership sets the tone - one firm now tracks senior executive calendar time dedicated to immersing in AI as a KPI!
Where should telcos apply generative AI to maximise value with those enablers in place? Our research and client work reveal four high-potential domains:
Of surveyed use cases, CX generated the most tremendous confidence in ROI. Conversational AI and agent assistants already smooth operations - consider the Latin American firm improving service by 25%. Cognitive contact centres that handle complex interactions could transform satisfaction and loyalty.
Personalisation powered by generative AI drives demonstrably higher campaign performance. Content generation streamlines product development cycles. Both lift revenue and reduce costs. Firms are already targeting 10-40% gains in the next few years.
Integrating Silicon Valley innovation into the telecoms backbone promises enormous potential - optimising buildouts, predictive maintenance, automated remediation and more. While complex, it is perhaps the most defensible source of competitive differentiation.
With technical debt surging at many firms, generative AI for documentation, testing, and especially code generation offers quicker, higher-quality software development. McKinsey finds over 100% developer productivity gains in early testing.
Despite measured optimism in the survey, exponential change may arrive sooner than expected. In the next 2-5 years, rapidly improving language comprehension, reasoning ability, and accuracy opens possibilities once only in science fiction.
We foresee conversational agents handling complex technical support tickets or sophisticated sales negotiations. AI assistants proactively optimise networks based on environmental conditions and usage trends. Customers perceive human-like warmth and nuance when engaging in self-service tools—and sweeping enhancements in automation, productivity and innovation across departments.
Challenges remain in areas like bias, security, and job impacts that require prudent management. But for an industry seeking revitalisation, becoming “AI native” likely represents the most credible path back to growth. Early movers are already stealing a march in unlocking this potential. With generative AI advancing daily and competition rising, can telecom leaders afford to wait any longer before fully committing themselves to this future? The clock is ticking.
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