Generative artificial intelligence (GenAI) is transforming businesses across industries and is poised to unlock new possibilities, enabling new avenues of innovation. Most business leaders are integrating GenAI into their customer service or deliverables to deliver a personalized and intelligent experience. They are also deploying solutions in their back-end operations to augment their workforce and optimize costs at scale. In the world of technology, media, and telecommunications (TMT), leaders are seeing the benefits that GenAI has to offer across different functions.
According to a recent survey According to our firm, more than half (55%) of TMT respondents say GenAI was among their top three investment priorities in the past 12 months. This pace is expected to continue, especially as GenAI, deployed as a scalable solution, has the potential to drive significant ROI and business transformation in the TMT industry.
Pre-implementation assessment of GenAI
Business leaders across all industries must critically assess their specific organizational goals to develop a GenAI approach that can have the greatest impact on their business model, operations, resource allocation, and product innovation. In the TMT world, leaders are already thinking about how to strengthen their GenAI approach alongside other emerging technologies. In fact, some TMT leaders have enlisted outside help to do so. Sixty-five percent of TMT executives said they have already hired or plan to hire a service provider to help them implement their GenAI strategy. However, before implementing any strategy, it is critical for TMT executives (and executives across all industries) to assess the organization’s business objectives. Assessing these types of objectives allows executives to implement a GenAI strategy or emerging technology strategy that is tailored to their unique business needs.
Trust by design analysis is also another important factor. It is the essence of any successful business in a world that values trust. Leaders, who are trying to build a GenAI-based business, must establish robust evaluation techniques that assess the quality of the results generated. Validation of models is imperative before their large-scale implementation. For this, regular monitoring of results should be considered a priority. Stakeholder feedback should also be a key data point in determining the benchmark for trust by design.
The challenges facing the TMT world
Like any evolving technology, there will likely be challenges along the way for companies to structurally leverage the latest technological innovations. While some TMT companies are accelerating GenAI adoption at a measurable pace, 48% TMT leaders still face challenges in launching their GenAI strategy. Externally, TMT leaders mentioned that uncertainty in legal and regulatory environments, industry disruption, and lack of trust in GenAI from external stakeholders are creating challenges for GenAI adoption. Internally, TMT companies face challenges such as difficulty identifying and managing GenAI risks. According to a report Recent Pulse Survey77% of TMT executives cite a lack of relevant skills among their workforce as a moderate or serious risk. This can be a cause for concern, especially as many companies plan to invest in emerging technologies like GenAI to drive growth. Thirty-three percent Technology and telecommunications executives also cited not having the right capabilities among their workforce as one of the top three reasons why their technology investments are not delivering the expected results.
To begin addressing some of these issues, leaders should consider adopting a responsible approach to AI. This approach prioritizes a responsible approach to managing the risks associated with an AI-based solution. It also helps leaders prepare for future challenges, such as impending regulations.
GenAI at Scale: Things to Consider
To improve investments in GenAI, leaders are now thinking about how to not only integrate but also extend the use of GenAI across functions and structures. Business leaders are thinking beyond strategy and want to ensure that their organization’s culture fosters innovation, collaboration, and new learning opportunities across teams. Currently, only 8% of TMT companies surveyed According to OECD data, over 40% of their employees are involved in developing, launching, adopting or commercializing emerging technologies as part of their primary job function. To address this gap, 34% of TMT executives have trained some employees in key roles needed for GenAI and 36% plan to do so in the next 12 months. This type of upskilling has the added benefit of increasing retention rates, which is a challenge for the industry.
Additionally, it is also important for leaders to look beyond individual use cases to help drive ROI. Developing AI programs offers opportunities for scalability and cost efficiency, particularly through in-house AI factories. AI factories are comprised of data scientists and engineers as well as business analysts and skilled GenAI professionals who work to refine the model and customize the results to deliver responsible outcomes. Essentially, AI factories with multidisciplinary representation help create the foundation for a responsible framework.
Last but not least, trust is a must-have design to scale successfully. A trusted and secure GenAI environment is surrounded by safeguards and governance, guided by responsible AI practices, to foster data integrity and intellectual property. This includes building on established governance, cybersecurity, privacy, and compliance programs and, at times, engaging in data infrastructure modernization efforts. Currently, 30% of TMT sector executives have already implemented governance measures for responsible GenAI development and deployment, while 28% have adopted cybersecurity and privacy enhancements. By prioritizing responsible implementation, organizations can effectively mitigate risks, foster trust among stakeholders, and capitalize on the vast opportunities offered by GenAI.
New heights and beyond
To effectively and efficiently deploy GenAI in organizations, especially in the TMT space, it is important for leaders to reassess their business needs, invest in skilled AI personnel, and prioritize responsible AI to build trust. Developing a well-structured AI governance operating model with holistic policies and standard operating procedures, as well as assessing readiness for compliance with current or upcoming regulations can go a long way in building trust. Additionally, leaders must actively foster and nurture a community that encourages and fosters a culture of creativity and collaboration with GenAI. By focusing on these factors, leaders will be more likely to realize substantial returns on investment and propel organizational growth and innovation to new heights.
