Managing the challenges of AI

Managing the challenges of AI

Artificial Intelligence (AI) is reshaping industries, from healthcare and banking to retail and telecommunications. But while the opportunities are huge, the road to success is not straightforward. Many businesses still struggle to move beyond pilot projects and experiments to reach scaled, production-ready deployments that truly deliver value.

IDC’s Business Value Solution Brief on VASS Intelygenz provides a timely perspective on these challenges and how they can be overcome. The research is based on in-depth conversations with organizations already working with Intelygenz. It explores what’s working, what obstacles remain, and what lessons other businesses can draw. The report shows that with the right support and approach, AI can help companies accelerate time to market, increase productivity, and even open entirely new revenue streams.

At the heart of the IDC findings is the tension between challenges and opportunities. Companies know that AI is essential for long-term competitiveness, but they are also grappling with issues such as skills shortages, difficulty aligning projects with business priorities, and the fast-changing pace of AI technology itself. Let’s take a closer look at what these challenges mean in practice and how businesses can overcome them.

Balancing the challenges and opportunities of AI

One of the clearest messages from the IDC report is that organizations often underestimate how complex it is to adopt AI at scale.

The main challenges include:

-Skills and knowledge gaps. Many businesses simply don’t have enough in-house AI expertise to develop and maintain effective solutions. Smaller organizations in particular lack the budget or resources to hire large AI teams.

-Aligning AI with business priorities. It’s easy to get caught up in the hype of Artificial Intelligence, but without clear alignment with business goals, projects often stall or fail to deliver measurable impact.

-Integration with existing business software. Legacy systems, fragmented data, and outdated infrastructure make it difficult to embed AI smoothly into daily operations.

-The fast pace of change. AI evolves rapidly. Keeping knowledge up to date and scaling delivery capacity without losing quality is a continuous challenge.

Yet despite these hurdles, the opportunities are too significant to ignore. IDC highlights how organizations working with Intelygenz achieved major benefits:

-61% quicker project completion. AI-related projects moved from concept to delivery much faster than before.

-43% faster go-to-market with AI applications. Companies could launch AI features ahead of competitors, capturing early market share.

-30% increase in application usage. Internal and external users were quicker to adopt AI-powered tools because they worked well and solved real problems.

$410,000 annual productivity rises. By improving IT team efficiency, Intelygenz delivered tangible financial returns.

These figures show that while AI adoption comes with obstacles, the payoff is worth the effort. With the right strategy and support, businesses can move from trial-and-error experiments to scaled, high-value applications.

How to manage challenges with the AI Academy

One of the most practical solutions highlighted in the IDC report is the AI Academy. This initiative is designed to bridge knowledge gaps, build confidence, and align teams around realistic AI strategies.

Many organizations fall into the trap of confusing automation with AI. For example, a task where 90% of the steps follow predictable patterns may not need an advanced AI model at all — simple automation may be more effective. The AI Academy helped participants make these distinctions, saving time and resources while focusing AI investment where it could deliver the most impact.

Key benefits of the AI Academy include:

-Clarity and focus. Teams learned to separate automation from true AI, ensuring projects matched the right technology to the right problem.

-Faster readiness. By building foundational knowledge, staff gained confidence to experiment with AI tools and processes.

-Iterative thinking. Instead of betting everything on a single big project, organizations learned to test, refine, and scale gradually.

-Executive buy-in. Senior leaders gained a clearer understanding of AI’s potential, leading to smarter investment decisions and stronger alignment with business goals.

One organization interviewed by IDC described the academy as a turning point. By applying the lessons, they discovered that many routine processes could be automated quickly, freeing their skilled teams to focus on areas where AI could drive real innovation. That clarity prevented wasted investment and delivered early wins that built momentum across the company.

Another organization noted that the academy helped their leadership team shift from skepticism to advocacy. By learning the basics of AI in an accessible way, executives were better prepared to champion projects and ensure funding was aligned with long-term strategy.

The lesson is simple: education and structured learning are essential to managing AI challenges. The AI Academy shows that success doesn’t come from technology alone, but from empowering people to use it wisely.

Key lessons for other industries

The IDC report makes clear that the challenges Intelygenz clients face are common across industries. Whether it’s a bank, a telecoms company, or a software provider, the underlying issues are remarkably similar: lack of skills, difficulty scaling, and the risk of projects failing to deliver.

Take financial services as an example. Banks are under constant pressure to balance innovation with compliance and risk management. Introducing AI into processes like loan approvals or fraud detection requires not just technical expertise but also strict adherence to regulatory standards. IDC found that Intelygenz helped one financial institution dramatically increase efficiency by enabling faster loan reviews. By automating parts of the process and applying AI intelligently, the bank could review more loans in less time, charge faster for services, and unlock new revenue opportunities.

In addition, Intelygenz solutions improved security operations. One bank reported a 90% increase in security team efficiency when monitoring and mitigating risks in AI applications. This is critical in a sector where data protection and compliance are non-negotiable.

The telecommunications industry offers another example. Here, companies deal with high volumes of customer service requests and complex incident responses. Intelygenz applied AI as a kind of “traffic cop,” routing issues to the right teams and reducing response times. The result was not only better customer satisfaction but also a lighter workload for employees.

These case studies highlight that the real challenge for industries is not whether AI can deliver value — it clearly can — but whether organizations can manage the journey effectively. That means:

-Choosing partners who understand both AI technology and the specific demands of the industry.

-Building internal capabilities so staff can sustain and scale solutions.

-Embedding AI into existing business software without disrupting operations.

Intelygenz’s collaborative, experimentation-first approach addresses all three points. By acting as a trusted extension of client teams, they reduce risk, accelerate time to value, and ensure that the benefits of AI are not short-lived but sustained over time.

Broader business implications

Another striking aspect of the IDC report is the range of quantified business impacts. These go beyond IT efficiency to touch nearly every part of the organization.

-Customer support productivity increased by 83%. With AI-driven tools, support teams handled more queries, faster, without increasing headcount.

-Data analytics teams became 90% more productive. AI-powered automation cut the time needed to create reports, allowing analysts to focus on deeper insights.

-C-level productivity rose by 15%. Executives could align strategy with AI investment more efficiently, reducing the time spent on decision-making.

-Audit operations improved by 30%. AI streamlined auditing processes, cutting manual effort and improving accuracy.

These gains illustrate that AI adoption is not just about cost savings. It’s about creating new capacity for innovation, better customer experiences, and more strategic use of resources.

Key outcomes of the report

AI adoption is one of the defining business challenges of our time. The IDC report on VASS Intelygenz shows that while the obstacles are real — skills gaps, alignment difficulties, and the relentless pace of change — they can be overcome.

The key is to approach AI strategically. That means:

-Recognizing that experimentation and learning are part of the journey.

-Investing in education through initiatives like the AI Academy.

-Partnering with experts who can bridge the gap between business priorities and technical execution.

-Embedding AI into existing business software in ways that enhance, rather than disrupt, operations.

For companies willing to take this approach, the rewards are significant: faster time to market, measurable productivity gains, new revenue opportunities, and a stronger competitive edge.

As IDC concludes, organizations that align AI with business goals while building long-term capability will not just survive the AI revolution — they will lead it. And with partners like Intelygenz, managing the challenges of AI becomes not a barrier, but a pathway to transformation.

Download the full IDC report here