Practical strategies for enterprise AI adoption
Whether you're using artificial intelligence (AI) to generate meeting notes, draft emails, or screen candidates—there’s no denying that it’s become a transformative force in the global business world. From manufacturing to retail, companies are using AI to streamline operations, improve customer experiences, and reach new markets.
In fact, a recent survey found that 90% of enterprise decision-makers said their companies are already using AI in some capacity—while 47% said they see AI as a leading driver of productivity.
Yet, the risks of AI adoption are real. PwC’s Annual Global CEO survey 2024 found that 77% of CEOs are concerned about AI security, and for good reason. The rise of “AI smugglers”, aka employees who bring their personal AI tools into the workplace, is creating new security and operational challenges.
However, the arrival of Generative AI (GenAI) has reinvigorated the AI landscape, ushering in a new era of possibilities and fundamentally changing the way people engage with technology. Not only is GenAI more accessible—it can be used to amplify the impact and value of other technologies.
In DeepL’s recent webinar on enterprise AI adoption, we had the privilege of speaking with guest industry experts J.P. Gownder, VP and Principal Analyst at Forrester, and Klaus Schmidt, Partner and Alliances Leader at PwC. Both shared insights on the latest trends, challenges, and opportunities in AI implementation.
In this blog post, we’ll summarize the webinar’s key takeaways and explore how your enterprise can:
Build a strong business case for AI adoption
Mitigate AI risks
Invest in AI skills and preparation
To get the full experience and learn directly from AI industry experts J.P. and Klaus, check out our on-demand webinar.
Trends in AI adoption
In 2024, GenAI is no longer a niche use case; it can generate realistic text, images, and code. And enterprises have noticed. Fueled by a rapid increase in AI spending, enterprises are investing in GenAI to transform operations, scale, and stay competitive.
According to Forrester’s Q2 2024 AI Pulse Survey, 33% of AI leaders believe that more than half of their company’s non-technical workforce will be using GenAI by the end of this year. Such a fast adoption rate points to a certain level of optimism from leaders.
Moreover, Forrester has also forecast that GenAI software spending will reach a staggering $124 billion by 2030, for both generalized and specialized adoption. Clearly, GenAI is here to stay.
Driving productivity with AI
One of GenAI’s most significant impacts? Productivity. According to Forrester's AI Pulse Survey 2023:
34% think AI will increase automation of internal processes
33% believe AI will improve operational efficiency and effectiveness
32% think AI will increase employee productivity
By leveraging AI, businesses can streamline workflows, reduce manual labor, and optimize resource allocation—all resulting in productivity gains.
The impact of AI on productivity is not limited to specific departments or functions, but has the potential to affect a wide range of roles. For example, AI-powered tools can help customer service teams handle routine inquiries, freeing up human agents to focus on more complex tasks that require empathy and critical thinking.
Overall, GenAI allows enterprises to do what matters most: stay ahead of the competition.
Building a business case for enterprise AI
For successful enterprise AI adoption, you need to build a strong internal business case—one that makes a clear cost-benefit analysis.
It’s important to use a comprehensive framework that includes factors such as:
Employee salaries
Cost of acquiring and maintaining AI solutions
Time savings that AI can provide
By considering these factors, in addition to other related costs such as tool management and training, you can get a clearer picture of the financial impact of AI adoption.
Yet, not all benefits of AI are so easily measured. For example, the potential for improved collaboration, heightened creativity, and error reduction are equally significant but more challenging to quantify.
Looking to pitch AI solutions at work? To explore J.P. Gownder's simple, effective AI business case calculation—with quantifiable metrics and advice on how to measure qualitative data—watch the full webinar.
Risks and opportunities of AI adoption
AI offers immense potential, but it also comes with inherent risks that require careful consideration. Successful AI adoption requires alignment across data, technology, business processes, and people.
According to Forrester’s research, there are many barriers to GenAI adoption:
30% cite a lack of technical skills
28% cite difficulty integrating with existing infrastructure
28% cite data privacy and security concerns
In the words of Forrester’s J.P. Gownder, we should also be wary of “AI smugglers”:
“[. . .] on the bring-your-own AI front, the best thing you can do is to equip people with formal sanctioned tools that allow them to not go to use their own tools. You need to give people options to take advantage of these opportunities.”
Additionally, another Forrester study highlights the risks surrounding governance, with 56% of respondents citing the potential for misuse of GenAI outputs—which can lead to errors or violations of data protection laws. Thus, proofreading and editing GenAI output is critical to mitigate these risks and provide accurate, reliable results.
Despite these challenges, GenAI offers many opportunities for businesses to achieve operational excellence and growth. When used properly, GenAI can elevate, empower, and engage both employees and customers—leading to increased job satisfaction, superior customer experiences, and ultimately, better business results.
Skills and preparation
AI is developing so fast that many businesses can struggle to keep up. To close this gap and achieve value faster, employee training, communication, and change management are critical.
With AI today, we’re moving from deterministic computing, where there was a 1:1 correspondence between command and output, to probabilistic AI, where we don’t always know what to expect from output. Here, upskilling employees is critical as GenAI systems become more central to decision-making.
To J.P. Gownder's estimation, for many companies, “leaders may believe that their employees are more ready than they are, or less ready that they are.” Either way, it’s a leader’s job to assess their employees’ knowledge levels.
To help organizations understand their readiness for AI, Forrester introduced the concept of the Artificial Intelligence Quotient (AIQ). The AIQ measures employees’ ability to use AI effectively and includes four key components, which are explored in full in our Enterprise AI playbook webinar.
What it all means for your enterprise
To succeed, enterprises need to consider the potential of human-AI collaboration, which—when done right—can lead to exceptional results.
Here, the employee experience (EX) is central to successful enterprise AI adoption. Engaged and satisfied employees are more productive, loyal, and more likely to embrace new technologies. By prioritizing high EX in AI deployments and involving employees in the creation of new AI-driven workflows, businesses can amplify the benefits of AI and foster a culture of innovation.
According to Forrester’s J.P. Gownder, AI isn’t about replacing humans, but rather enhancing human capabilities to drive productivity. To prepare for the future of work, businesses should invest in skill-building initiatives, change management programs, and continuous employee development.
Watch the full webinar: building an AI adoption strategy
Dive into even more insights with DeepL’s Q&A session between Gownder, Schmidt, and DeepL’s CMO, Steve Rotter. Together, they discuss key considerations for successful GenAI implementation and the challenges of managing an ever-growing number of workplace tools and data sources.
The trio covers questions such as:
What are the top three best practices enterprises should adopt when working with AI?
How do you measure a company’s AI readiness?
How do you deal with the increasing amount of tools in the workplace?
AI is no longer a nice-to-have—it’s a must-have. And regarding AI adoption, Klaus Schmidt shares:
“If you think you have everything under control you’re probably not going fast enough.”
Enterprises must adapt and innovate with speed—recognizing that AI is not just a tool, but a powerful driver of growth and transformation. By embracing AI technologies, businesses can unlock new opportunities and chart a path to future success.
Watch the full webinar now to hear from J.P. (Forrester) and Klaus (PwC) directly. Discover what their own research and day-to-day interactions with customers have taught them—and use their insights to help your organization jump-start its own AI implementation strategy.
