The technology, media, and telecom (TMT) sector is a leader in GenAI adoption, with 52% of TMT companies already leveraging its capabilities, according to the EY Work Reimagined Study 2023.[1]
As a sector that thrives on the rapid development and deployment of cutting-edge technologies, TMT companies are often already equipped with the necessary infrastructure, technical expertise, and data ecosystems to integrate GenAI into their operations. Early adoption of GenAI gives TMT companies a significant advantage in exploring GenAI’s potential and navigating its challenges for both current and future benefits. Technology providers are enabling GenAI solutions, telcos are building necessary infrastructure, and media companies are poised to innovate and disrupt traditional business models. This trend is reflected in 45% of TMT firms investing in AI-driven innovation and another 46% planning significant investments.
Internally, TMT companies are using GenAI to revolutionize systems and processes. The high adoption rate underscores their readiness to integrate GenAI into operations and services. Although media and entertainment companies face slightly lower employee usage rates, indicative of some resistance, the sector as a whole is well-positioned to deploy GenAI effectively.
Yet, being at the forefront of GenAI adoption, TMT companies face several challenges. They must navigate evolving regulations such as the upcoming EU AI Act, integrate new GenAI partnerships into existing ecosystems, and contend with economic conditions that may limit AI investment. Additionally, they have to manage employee and customer resistance due to concerns over data privacy and job displacement. Effective data management is also crucial for training GenAI algorithms, addressing the complexities of data fragmentation, and ensuring robust data governance.
Five no-regret actions for TMT companies
To overcome these challenges, there are certain actions TMT firms can take.
1. AI control tower. To fully harness the potential of GenAI, companies should consider establishing an AI control tower, which involves creating a centralized group to drive AI innovation, governance, and skill centralization. Immediate actions include designating a C-suite executive as an AI leader, identifying relevant skills and immediate skills gaps, and developing a portfolio of targeted GenAI opportunities.
2. Reimagine business functions: Businesses should reimagine their functions by using GenAI to enhance productivity and reshape workflows. This can be initiated by launching small-scale pilot projects using proprietary data, creating internal feedback loops with the AI control tower, and communicating clearly with employees about workflow changes.
3. Ecosystem strategy: An ecosystem strategy is also crucial, requiring companies to adapt existing ecosystems to leverage GenAI opportunities. This involves prioritizing AI discussions with existing partners, identifying new partners for GenAI initiatives, and assessing GenAI readiness across different infrastructure layers.
4. Build stakeholder confidence: To build stakeholder confidence, it’s important to implement ethical frameworks and governance to address AI-generated risks and concerns, which includes identifying and mitigating new risks from GenAI, implementing ethical AI procedures and monitoring tools, and addressing GenAI data privacy concerns for enterprises.
5. Tech transformation: Tech transformation is key, and companies should integrate GenAI into broader technology transformation programs. Actions to take now include prioritizing technology deployments based on business strategy, preparing datasets for specific GenAI use cases, and ensuring the availability of cloud and compute infrastructure.[2]
Use cases for GenAI in TMT
TMT companies have found various applications for generative AI. These use cases include the enhancement of customer service with more intelligent chatbots and tailored offerings. Additionally, generative AI is instrumental in creating innovative business models by refining service platforms, as well as supporting product development and distribution. The technology also plays a significant role in boosting productivity and automation, leading to more effective knowledge management and freeing up time for innovation.
In Luxembourg and Europe, there is a noticeable trend of firms adopting generative AI for diverse operations. For instance, there have been cases where companies have improved their sales processes by using GenAI in conjunction with tools like Microsoft Copilot. Such integration allows artificial intelligence to interpret intricate client data, which in turn facilitates the automatic generation of accurate fee quotes. This not only streamlines the sales process but also minimizes the need for manual data input.
The use of generative AI extends to IT Service Management (ITSM) workflows as well. With the help of tools like Copilot, the management of a high volume of IT support tickets can be automated. This automation assists back-office teams by pre-populating ticket information and enhancing the efficiency of the support process.
TMT companies are well-placed to leverage GenAI’s transformative potential. By addressing challenges head-on and implementing strategic GenAI use-cases, they can drive innovation and efficiency. A focus on ethical practices, robust data governance, and strategic partnerships will be crucial in maintaining their lead and maximizing GenAI’s long-term benefits.
[1] EY, Work Reimagined Study 2023, EY Knowledge Analysis
[2] Five “no regret” actions for TMT companies to unlock generative AI’s potential, EY, November 2023
