Overcoming Hesitation and Harnessing the Power of Generative AI

An exciting new era has arrived. Thanks to content-creating tools like ChatGPT, Midjourney and Bard, Generative AI (GenAI) has captured the public's imagination with its impressive creative abilities. The emergence of these tools marks a significant milestone in the technological landscape; AI has become democratised, with users no longer needing an AI degree to derive value from using it. The extraordinary nature of this has led to much hype, but for business leaders, questions remain about the long-term business value and potential associated risks. When it comes to GenAI, leaders face challenges in effectively integrating it into their business in a meaningful, beneficial, tangible way.

We see evidence of this dichotomy in our recent GenAI Pulse Survey results. When we polled IT Decision Makers (ITDMs) in the UK, we discovered that many are excited by the prospect of GenAI and its transformative capabilities for their organisation. Seventy-five percent of UK ITDMs believe GenAI will significantly transform their organisations, with these 'transformations' including streamlining processes (21%), revolutionising productivity (15%), and achieving cost savings (19%), all of which would drive positive long-term business outcomes.

Equally, it appears that organisations have made good progress in their GenAI journey. In fact, of those who have moved beyond the pilot stage, an impressive 81% believe that GenAI is well on its way to delivering meaningful results for them. Many (80%) report implementing centralised decision-making and/or centre of excellence (COE), signalling substantial investment in this technology relatively early in its inception.

Yet, despite this, nearly half (49%) expressed at least some level of hesitation about adopting GenAI. While there is significant momentum behind the technology, leaders are struggling to commit wholeheartedly, and this is a problem if businesses are to adapt and survive through the AI era.

So, what exactly is holding leaders back, and how can these issues be overcome in favour of harnessing innovation and positive change?

Concerns about employee morale

The most concerning aspect of GenAI adoption for business leaders is its potential effect on workforce morale (49%). Given the numerous headlines and debates about AI – its rapid advancement, ground-breaking abilities, and questions over its impact on the job market – it is perfectly logical for leaders to worry about employee optimism and confidence.

However, the reality is that GenAI is designed to augment human capabilities, not replace them. This crucial message needs to be communicated effectively to employees, especially during the early stages of adoption. Perhaps the best way to do this is to demonstrate, through adoption, the value of GenAI to human experiences in the workplace.

Digital employee experience (DEX) services can help businesses identify different GenAI use cases. By uncovering the needs, preferences, and potential impact of GenAI on different user groups, ITDMs can ensure that the right licenses, devices, and peripherals are deployed strategically, optimising spending and productivity, streamlining workflows and simplifying time-consuming tasks. GenAI tools such as Microsoft 365 Copilot augment employees' day-to-day workflows, helping to accelerate creative processes and quickly discover insights and correlations within reporting and testing. Giving teams access to new AI systems lets employees see firsthand how AI can improve productivity and make time-consuming tasks much more manageable. It's a powerful way to introduce employees to the potential of AI and showcase its value as a tool for enhancing their job performance.

Employees who consume GenAI capabilities built into application stacks like CoPilot will grow confident enough to explore other options, and DEX services can help the business ensure it meets its employees' technology needs. However, it will also take leadership across the C-Suite to change how the organisation thinks about work. Fostering open communication with teams and helping them understand what skills they need is critical, as is creating space for employees to test and learn how GenAI could positively impact their working experience.

Security fears

For decision-makers, the second most concerning aspect of GenAI is data security. We know that GenAI can be a tool for shoring up defences, but its very existence creates new volumes of data that become harder to protect and more readily targeted.

To successfully and safely manage and gain value from these new volumes of data, organisations should consider a consistent multicloud strategy with robust cyber resilience capabilities across public cloud ecosystems, private cloud, and the edge. In a world where it's a case of when, not if a business experiences a cyberattack, organisations can only confidently innovate at pace if they know they can restore a minimum viable enterprise and get back to business as quickly as possible.

There are many potential risks when hosting GenAI models in public clouds: intellectual property loss, data leakage, privacy issues, compliance violations, credibility and integrity loss, bias, and IP infringement. It's no surprise with these challenges that 76% of UK decision-makers said they preferred being mainly in the data centre on-premises or a hybrid model based on the data and its sensitivity. Bringing AI to the data (whether in the data centre or at the edge) gives organisations more control over their models, achieving better results and managing costs and security concerns.

The added risks associated with AI necessitate cybersecurity being prioritised as part of a broader AI strategy. This means thinking about AI and the resources that it uses not just from a technology perspective, but from a business perspective; people and processes remain vital elements of the overall strategy. It is incumbent upon leaders to understand how people respond and interact with GenAI. On the one hand, the workforce needs to be upskilled and re-educated to cope with the emerging security risks and opportunities around AI. On the other, we must also get our heads around threat actors' tactics, techniques, and procedures - knowing how attackers will come at our AI workflows will give organisations an advantage, enabling IT decision-makers to put the proper controls in place at appropriate points in the organisation.

Technical complexity and cost

Finally, leaders listed technical complexities (39%) and cost of implementation as other significant concerns (35%) hindering their AI journeys. While it's true that GenAI is not a simple add-on to existing infrastructure – successfully implementing GenAI involves taking a holistic approach that includes intricate system design and a deep understanding of the nuanced hidden costs – ensuring cross-team collaboration between department business leaders and IT can help make 'complexities and cost' more manageable.

IT teams should partner closely with CXOs and other departments to ensure the business understands the broader implications of GenAI on the IT ecosystem and what this might mean for day-to-day operations. Likewise, they need to work with HR and recruitment to ensure the right talent with the right skill sets are in place. Hiring talent can be expensive, as can investing in training and upskilling. However, as we have explored, GenAI can assist in quickly upskilling talent by enabling more personalised training programmes tailored to unique learning styles and paces. IT is often best placed to consult on these needs and advise on available solutions and should be an instrumental part of this broader collaboration between teams.

When aligning business and IT teams, organisations should look beyond simply improving internal operations and adopt a multifaceted perspective. IT can help evaluate how to integrate AI into products,

transform processes, utilise infrastructure, and collaborate with partners. In essence, true business transformation.

Summary

There is a delicate balance between embracing the much-anticipated potential of GenAI and addressing its challenges. The fear, uncertainty, and doubt employees feel in the face of GenAI are not reasons to slow down, but they are concerns that need to be addressed to future-proof one's organisation. Likewise, while security, complexity and cost challenges make capitalising on the potential of GenAI easier said than done, it must be done. IT leaders must make critical decisions about what GenAI applications they run and where, carefully consider the compute and storage they need and decide on the architecture that will situate and run them.

The pace at which GenAI seems to be becoming a non-negotiable part of futureproofing can be overwhelming, as it's so unlike anything we have ever seen. Thankfully, many vendors offer free guidance on GenAI target use cases, data management requirements, operational skills and processes and can help define a business’s key opportunities, challenges, and priorities. Embracing broader toolsets and data sources through an open ecosystem of partners who can provide AI expertise and services may well be the best way for businesses, large and small, to manage the obstacles that stand in the way of true GenAI ROI.