Using GenAI Strategically Is Riskier, but It Pays Off

• Many middle market firms use GenAI for low-impact tasks, limiting their ability to achieve significant business outcomes.
• The top challenges to GenAI adoption — integration complexity and high costs — highlight the need for more comprehensive support and training.
• Strategic uses of GenAI enhance efficiencies and innovation, driving higher ROI, improved effectiveness, and competitive advantage.
• This edition also features an interview with Christoph Rabenseifner — Deutsche Bank's chief strategy officer, technology, data and innovation — on the bank's GenAI journey.

Generative artificial intelligence (GenAI) holds immense potential for transforming how organizations deploy technology to improve operational efficiency and drive innovation. Still, many firms fail to fully leverage the technology’s capabilities. For example, half of surveyed chief marketing officers (CMOs) use GenAI for routine tasks like drafting emails and visualizing data. Just 20% use it for more strategic initiatives. However, organizations using the technology more strategically report the highest returns on investment (ROI). By overcoming integration challenges, investing in training and fostering a supportive environment, savvy organizations can realize greater value from GenAI.

• Middle-Market Firms Use GenAI Mostly for Routine Tasks
• GenAI Integration Tops CFO Concerns
• Positive Impacts on Efficiency and Innovation
• Overcoming GenAI Integration Challenges
• Deutsche Bank’s GenAI Journey

Middle-Market Firms Use GenAI Mostly for Routine Tasks

While all middle-market firms report using GenAI, most apply it to routine or low-impact tasks. This trend is particularly evident in the telecommunications industry. For example, communications service provider (CSP) Amdocs found, in collaboration with Analysys Mason, that most CSPs focus on low-impact use cases. These include marketing content creation, co-pilot-style query generation and text summarization.

Likewise, middle-market firms’ heavier reliance on GenAI for low-impact tasks over more strategic ones reflects broader adoption trends. For example, 4 in 5 CMOs use the technology to support market research. This use of the technology suggests that while firms recognize the potential of GenAI, they’re still testing its capabilities and benefits on basic applications. However, taking a cautious approach reveals that these firms are also more likely to miss out on the technology’s transformative applications.

Executive support is key to deeper GenAI adoption.

Firms that report using GenAI less strategically are also 50% more likely to report a lack of executive support. This support is key to wider organizational adoption of the technology. One-third of CFOs face this issue, with a larger share (48%) at low-impact firms lacking executive backing. In contrast, high-impact users were more likely to report elevated levels of concern about data security (56%) and high costs (61%). Finally, medium-impact firms struggle with tools that are difficult to use (52%) or confusion about which ones to choose (43%).

GenAI Integration Tops CFO Concerns

Enterprise users report integration complexity and high costs as primary drawbacks of GenAI adoption. More than half of executives at midsize firms in the U.S. and Canada cite difficulties in rolling out these technologies, mentioning employee buy-in, implementation of new processes, additional training and data privacy concerns.

Middle-market firms face challenges like the initial costs and integration risks of implementing advanced GenAI solutions. For their part, CMOs cite high costs (27%) and integration complexity (42%) as major drawbacks to the adoption of the technology. Likewise, CFOs from middle-market firms, often operating within tighter budgets than their larger counterparts, may find it challenging to allocate significant resources to complex GenAI initiatives.

Comprehensive training and support are essential.

Notably, 2 in 5 firms on the fence about GenAI cite data security or integration challenges as drawbacks to adoption. The prevalence of these obstacles highlights the need to address them to maximize the technology’s potential.

Overcoming these challenges requires a multi-faceted approach. Companies need to invest in comprehensive training programs to equip employees with the necessary skills and knowledge to use GenAI effectively. By doing so, firms can reduce resistance to GenAI adoption and ensure smoother integration into existing processes.

Positive Impacts on Efficiency and Innovation

More than three-quarters of enterprise CFOs using GenAI strategically report positive impacts on internal efficiencies and innovation capacity. Firms like Shift Technology achieve significant accuracy and efficiency improvements in claims processes through GenAI solutions. These applications enhance operational efficiency and foster innovation, showcasing GenAI’s transformative potential. The deeper integration of GenAI into business processes allows firms to capitalize on its full capabilities, driving more substantial improvements.

High-impact GenAI users leveraging the technology for strategic initiatives, such as marketing strategy and brand management, are seven times more likely to report very positive ROI. This highlights the value of using GenAI for high-impact applications aligned with the company’s strategic goals.

Strategic GenAI use enhances firms’ competitive advantage.

Nearly 4 in 5 CMOs consider GenAI very or extremely important for providing a positive customer experience. Likewise, its value to product marketing and marketing analytics illustrates its utility in supporting data-driven strategies. GenAI aids comprehensive planning in marketing strategy, advertising and promotion. Brand management and lead generation highlight GenAI’s role in maintaining brand identity and driving sales. This emphasis on GenAI’s importance across functions shows its growing impact on enterprise marketing practices.

Deutsche Bank’s GenAI Journey

As chief strategy officer, Christoph Rabenseifner has worked to build up Deutsche Bank’s business division of technology, data and innovation since 2019. He is responsible for the division’s vision and strategy, including areas such as artificial intelligence and the cloud.

Deutsche Bank’s journey with GenAI began in earnest in 2022. The German lender’s innovation team led the initiative, collaborating across all areas of operations.

“Our central innovation team works closely with all areas of the bank to promote the understanding of how modern technologies — in particular artificial intelligence — can be applied,” said Rabenseifner.

As a result, Rabenseifner’s team explored how GenAI, as a subset of AI, could be leveraged for various applications. The team collected several hundred ideas and identified common usage patterns, which are currently being tested in pilot programs. As these pilots advance to production, scalable AI services are being established to enable rapid implementation of similar applications across the bank.

The biggest challenge in this effort, said Rabenseifner, has been ensuring that the technology adds real value to the firm. This involves evaluating whether the total cost of AI is justified by its benefits. This process requires a clear articulation of business impact, technology costs and potential risks. Moving from a pilot program to production demands significant cross-divisional collaboration, especially in security and data protection.

“We have established central AI strategy and oversight forums to ensure transparency across our portfolio, fostering safe implementation,” Rabenseifner noted.

These forums drive consistent architecture and accelerate adoption, according to Rabenseifner, unlocking value creation across the organization. While GenAI is expected to significantly improve internal processes and service quality, the full benefits have yet to materialize. Rabenseifner shared his vision for these benefits on the horizon.

Ensuring trust and reliability in GenAI applications is crucial. Looking ahead, the bank plans to make AI an integral part of almost all business operations. They will continue to explore business use cases, offer GenAI-powered shared services and create an AI platform for developers to build safe, controlled AI systems, said Rabenseifner.

We believe that in the future, AI will become an integral part of almost all aspects of our business operations, from internal processes to interaction with customers.”