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How to Manage AI’s Scalability to Accelerate Innovation
To expand the successful implementation of GenAI across organizations, leaders should reassess their AI strategy, invest in AI-skilled personnel, and prioritize responsible AI to gain trust.
5 Min Read
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Generative artificial intelligence (GenAI) is transforming businesses across sectors and poised to unlock more possibilities, fostering new avenues for innovation. Most business leaders are either embedding GenAI in their customer service or deliverables to provide a personalized, 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 by our company, more than half (55%) of TMT respondents say that GenAI was within their top three investment priorities in the last 12 months. This pace is likely to continue especially since GenAI deployed as a scalable solution has the potential to deliver and drive significant return on investment and business transformation in the TMT sector.
Assessing Before Implementing GenAI
Business leaders across sectors are obligated to critically assess their unique organizational goals to develop a GenAI approach that can make the most impact on their business model, operations, resource allocations, and product innovation. In the world of TMT, leaders are already thinking about ways to bolster their GenAI approach in addition to other emerging technologies. In fact, some TMT leaders have enlisted outside help to do this. Sixty-five percent of TMT executives said they have either already hired or plan to hire a service provider to help them with their GenAI strategy. However, before implementing any kind of strategy, it is paramount for TMT leaders (and leaders across sectors) to assess organizational business goals. Assessing these kinds of goals allows leaders to implement a GenAI or emerging tech strategy that suits their unique business needs.
Analyzing trust by design is also another important factor. It is the essence of any thriving business in a world that puts a premium on trust. Leaders, in trying to nurture a GenAI powered enterprise, need to establish strong evaluation techniques that can assess the quality of the output generated. Validating the models is imperative before implementing them at a scale. For this, monitoring the output regularly should be considered a priority. Feedback from stakeholders should also be an essential data point in deciding the trust in design benchmark.
Challenges Facing the World of TMT
Just like any evolving technology, there will likely be some challenges along the way as businesses structurally make room to benefit from the latest technology innovations. While some TMT companies are ramping up GenAI adoption at a measurable 48% , there are still challenges that TMT leaders face while kick-starting their GenAI strategy. Externally, TMT leaders have mentioned that the uncertainty of legal and regulatory landscapes, disruption of industries, and the lack of trust in GenAI by external stakeholders creates challenges on GenAI adoption. Internally, TMT companies face challenges such as difficulty in identifying and managing GenAI risks. According to a recent Pulse Survey, 77% of TMT executives cite a lack of relevant skills in the workforce as a moderate or serious risk. This can be a concern especially since many companies are planning to invest in emerging technologies like GenAI for growth. Thirty-three percent of technology and telecom leaders also cited not having the right capabilities among their people as one of the top three reasons their technology investments aren’t delivering expected results.
To begin to address some of these issues, leaders should consider taking the responsible AI approach. This approach prioritizes the responsible approach to management of risks associated with an AI-based solution. This approach also helps leaders prepare for future challenges, such as impending regulations.
GenAI at Scale: What to Consider
To improve GenAI investments, leaders are now deliberating on ways to not just integrate, but scale GenAI usage across functions and structures. Business leaders are thinking beyond the strategy and want to confirm that the culture of their organization fosters innovation, collaboration, and new opportunities to learn across teams. Currently, only 8% of surveyed TMT companies reported that more than 40% of their employees are involved in developing, launching, adopting or commercializing emerging technologies as part of their primary job function. To bridge this gap, 34% of TMT executives have trained select employees on key roles needed for GenAI and 36% plan to do so in the next 12 months. This kind of upskilling has the added benefit of boosting retention rates, which has been a challenge for the sector.
Additionally, it is also important for leaders to look beyond individual use cases to help drive returns. Developing AI programs offers opportunities for scaling and cost efficiencies, including internal AI factories. AI factories consist of data scientists and engineers along with business analysts and GenAI-skilled professionals who work to refine the model and customize the output to deliver responsible outcomes. Essentially, AI factories with multi-disciplinary representation help create the foundation for a responsible framework.
Last but certainly not least, there should be a foundation of trust in the design to scale successfully. A trusted, safeguarded GenAI environment is surrounded with guardrails and governance, guided by responsible AI practices, to help 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 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 presented by GenAI.
New Heights and Beyond
To scale the deployment of GenAI effectively and efficiently across organizations, particularly within the realm of TMT, it is important for leaders to reassess their business needs, invest in AI-skilled personnel, and prioritize responsible AI to gain trust. Developing a well-structured AI governance operating model with holistic policies and standard operating procedures, as well as assessing readiness to comply with current or forthcoming regulations can significantly contribute to building trust. Additionally, leaders should actively encourage 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 their investments and propel organizational growth and innovation to new heights.
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