By Jens Löhmar
Early adopters are reaping tangible benefits from AI implementation, with 82% reporting financial gains in a recent Deloitte survey. AI enhances products, operations, decision-making, and employee potential, prompting increased investments in cognitive technologies. However, AI adoption also brings a lot of challenges, both for CIOs and the company as a whole, such as privacy and ethics concerns. This article explores the key hurdles companies face and how to overcome them for successful AI results.
1. Data issues
The biggest obstacle to launching an AI project is data: Deloitte’s survey highlights that 16% of IT leaders ranked data issues as their top AI challenge, with 39% putting this in their top three areas of concern. This includes the lack of relevant, unbiased, and privacy-compliant data. Although companies routinely collect data, it might not be the right data. Another problem is not having the right data in the right quality and quantity. Focusing on high-value data pockets and value-driven exploration are therefore key. Often, scattered IT landscapes with dispersed data and even manual processes still prevent companies from kicking off AI & ML initiatives.
2. Implementation challenges
AI integration into business processes also presents significant challenges, as it is marked as the second biggest concern in the Deloitte survey. This includes technical complexities (39%) and addressing skill shortages (31%). As such, identifying relevant capabilities suitable for your business objectives, designing for exceptions, and enhancing team skills are essential for successful business transformation. Unleashing a technology’s full potential requires understanding. Here is where accessible on-demand learning, complemented by focus, time, and strategic prioritization comes in. It builds expertise, boosts confidence, and quickly addresses issues or questions. This, in turn, enhances engagement, productivity, self-reliance, and continuous learning, and opens doors for meaningful work and other tasks.
3. Cost of tools and development
Building AI systems from scratch is expensive in terms of labor and technology, particularly for newcomers. Without in-house developers, outsourcing is necessary. Deloitte reports that 59% of the companies source AI from software vendors and 49 percent use cloud-based AI. Vendors and cloud providers offer ready-made AI services, cutting costs and sparing the need for enterprises to build their own infrastructure and algorithm training. Also, cloud applications reduce infrastructure and internal support needs as well as administration staff.
4. Security, legal and regulatory risks
In the Deloitte survey, cybersecurity ranks as the top risk of AI. The complexity of AI makes risk evaluation and mitigation intricate, with the potential for malicious insiders contaminating training data and creating hard-to-detect flawed algorithms. Open-source libraries in AI applications further add risk, as malicious code can infiltrate the codebase. However, while data breaches can involve information about AI initiatives, they often stem from other vulnerabilities than in the AI application itself. AI is even progressively used for cyber defense. Furthermore, legal and regulatory risks are a significant issue for AI adoption. Implementing measures that enhance the transparency and interpretability of AI decision-making processes can enable better communication with regulators and stakeholders, reducing the potential for substantial penalties.
5. Ethics
Enterprises also worry about adopting AI prematurely. Deloitte’s survey reveals these worries: 32 percent cite ethical risks, 33 percent fear the possible erosion of trust from AI failures, and 39 percent highlight the possibility of AI system failures in critical situations. Technical teams implementing AI technologies are often in a position where they can see the potential risks early on and need to feel comfortable to bring them to the attention of the CIO, who can then take them to the board or an ethics panel. An open culture for discussing ethics is crucial for this.
Be aware of the digital acceleration gap
Technology advancements like AI challenge agility. Constant adaptability is vital for seizing opportunities and preventing setbacks. However, many struggle to keep up, which leads to an ‘acceleration gap,’ where organizations lag behind rapid changes. Expert guidance on leveraging technology investments for change management, risk reduction, and growth planning is therefore crucial – in addition to a flexible IT environment. Cloud-native platforms offer automated processes and a more resilient underlying architecture than legacy on-premise systems.
The CIO & agile workforce transformation
Talent management is changing, and being agile in response to that change is important. CIOs can guide their entire organization to prepare for the future of work by aligning technology with business needs and the capabilities of employees. IT paves the way for adaptability. However, with skills at the center of business transformation, close HR-IT collaboration is crucial.
With the help of AI and ML, together they can cultivate skill-based workforces, boosting adaptivity, resilience, and employee engagement. Unified systems empower businesses with the right insights and streamlined talent management. Furthermore, by automating routine tasks, CIOs can redirect talent to further improve customer experiences and boost revenue. This shift strengthens budget negotiations and safeguards crucial roles tied to business success.
Jens Löhmar is CTO of continental Europe at Workday
Workday is a leading provider of enterprise cloud applications for finance and human resources, helping customers adapt and thrive in a changing world. Workday applications for financial management, human resources, planning, spend management, and analytics are built with artificial intelligence and machine learning at the core to help organizations around the world embrace the future of work. Workday is used by more than 10,000 organizations around the world and across industries – from medium-sized businesses to more than 50% of the Fortune 500. For more information about Workday, visit workday.com.