Everything is being transformed by AI and digital platforms, including how teams are working together and how fast we can bring client results. It is not only automation. It's acceleration. One of the things consultants used to spend hours on is compiling data, cleaning spreadsheets, preparing decks. That grunt work can now be dealt with in a few minutes using AI tools. It is the equivalent of less time in the weeds and more time resolving real business issues. It is changing the consultant job to that of a strategist. It is also no longer a passive process of learning. Upskilling is infused into the labour process. Performance data on platforms help in determining knowledge gaps and deliver content that is relevant at this moment and not in a quarterly training program. It is not that people are learning faster, but also that they are applying what they learn in real-time. The future is no longer hypothetical anymore, human-AI teaming exists. You have analysts brainstorming with LLMs, auditors doing quality checks with predictive models, and managers doing decision-making with AI copilots. The companies who do this right will not only work faster, but they will think faster.
AI is changing the way consultants work by shifting their roles from task execution to a more strategic-based role. Since AI handles repetitive tasks, such as data analysis & compliance checks, consultants are now able to focus on creative problem-solving and building client relationships. For example, AI can help identify top candidates for a position but consultants should still evaluate other important qualities such as emotional intelligence & team fit. This shift will require consultants to gain new skills and familiarity with technical areas such as data analysis & AI ethics as well as other soft skills such as emotional intelligence and critical thinking. EY is focused on upskilling its teams to ensure they can work effectively with AI to help them adapt to clients' changing needs. The outcome is a more strategic, AI driven engagement which offers more value to clients.
With the entry of AI and digital platforms, we have revolutionized the way teams can work in cooperation, upskill themselves and serve patrons. Application of technologies like machine leaning and automation has led to the fact that activities that took longer to achieve earlier are accomplished in a fraction of that time. Workforces are able to work across borders and functions and can dedicate their time to work. The very tools provide new opportunities related to employees constantly upskilling themselves and keeping up with a technology environment that is constantly evolving at a fast pace.
New digital tools integrated with AI to help teams do their best work faster and better are evolving quickly, and changes are palpable at EY/Elikhani. These developments have allowed teams to make things easier, work more effectively and provide better quality of value to their customers. AI allows for tools that teach team members to upskill and better serve the organization and its clients. Along with automation, it has also contributed towards developing more collaborative and multi-faceted teams which have increased the innovation and problem-solving propensity of EY.
At EY, the rise of AI and digital platforms is changing the texture of daily work more than the structure. Internally, collaboration feels less like a chain of handoffs and more like a shared workspace that evolves in real time—tools like EY Fabric and Wavespace create continuity across time zones and functions. I've seen something similar happen at spectup when we introduced AI-supported diligence; suddenly, analysts and consultants weren't waiting on each other—they were building together. Upskilling is no longer a scheduled training exercise but embedded into workflows. One of their consultants told me how an AI-driven knowledge engine flagged real-time regulatory updates during a live client workshop—no need to "circle back" later. What's interesting is how human-AI teaming isn't about replacement; it's about rebalancing. Routine modeling, synthesis, and reporting are now accelerated, which frees up room for deeper strategic thought and creativity. Consultants are becoming orchestrators—guiding the AI, interpreting the outputs, shaping insights. The role is evolving toward influence rather than execution. At spectup, we faced something similar with pitch deck creation; once we automated some of the narrative structuring, it pushed us to focus more on storytelling and investor psychology. The real value now lies not in knowing the answer but in asking the smarter questions—something no AI can quite replicate yet.
While I haven't worked at EY specifically, I've led AI changes from both sides--as a Fortune 1000 IT leader implementing enterprise systems and now as a consultant helping businesses scale through AI marketing systems. The shift isn't just about new tools; it's about completely reimagining how work flows between humans and machines. At Riverbase, we've seen the biggest change in how teams structure their daily workflows. Instead of spending 80% of time on manual campaign setup and data analysis, our clients' marketing teams now spend that same time on strategic decision-making and creative problem-solving. One SaaS client went from taking 3 weeks to launch a campaign to launching optimized campaigns in 2 days, but their team didn't shrink--they redirected those hours into market research and customer relationship building. The upskilling challenge is less about learning AI platforms and more about learning to think in systems. When I scaled PacketBase to acquisition, the biggest learning curve was training our team to design processes that could run without constant human intervention. Today's teams need that same systematic thinking--not just "how do I use this AI tool" but "how do I design workflows where AI handles execution while I focus on strategy and exceptions." The role evolution is fascinating. Our enterprise clients are seeing their junior consultants become force multipliers almost overnight because AI handles the foundational research and data processing that used to take months to master. A manufacturing client's newest hire was presenting C-level insights within her first month because our AI systems had already done the heavy analytical lifting.
I've helped 32 companies implement AI across sales and marketing ops over 12 years, and the change isn't what most people expect. Teams aren't getting replaced - they're getting liberated from soul-crushing busywork. At one global client with 12,000 employees, we integrated AI into their Salesforce instance for lead scoring and pipeline management. Their sales reps went from spending 60% of their time on data entry to focusing purely on relationship building. Sales cycles shortened by 28% because reps could finally do what humans do best - read the room, build trust, and close deals. The real magic happens in what I call "microlearning moments." Instead of sending teams to week-long AI training bootcamps, we built AI assistants that teach on-the-job. When a rep encounters a complex lead, the AI doesn't just score it - it explains why and suggests next steps. Teams upskill naturally while working, not in sterile conference rooms. The consultants thriving right now aren't the ones who know every AI tool - they're the ones who can spot which 3% of tasks should stay human. I spend more time now identifying what AI should never touch than figuring out what it can automate.
I would like to mention that AI systems now track patterns across calendar usage, email sentiment, and even Slack rhythm to predict burnout or disengagement. These alerts enable EY team leads to reallocate workload before attrition becomes a threat, saving millions annually in unplanned turnover. For the first time in five years, global data breach costs have decreased. IBM's 2025 Cost of a Data Breach Report shows average costs fell to $4.44 million, a 9% drop from $4.88 million the previous year, driven by faster containment through AI-powered defenses. These signal trackers allow organizations to catch issues before they escalate, saving both time and money.
If you've ever wondered what it feels like to work at EY right now, imagine being part of a team where AI isn't just another IT trend, it's your teammate, your mentor, and occasionally the office DJ. Okay, maybe not that last part—yet. But here's the scoop: AI and digital platforms have totally re-written the script for how EY teams collaborate, learn, and show up for clients. EY has poured billions into AI, and it's not just about automating the boring stuff (though no one mourns data entry). It's about freeing people up for the creative, high-impact work, the kind that makes consultants proud to sign their emails. Take their "AI factory" and the EYQ generative AI platform: consultants use these daily to bounce ideas off chatbots, analyze tricky data, and draft client reports in record time. In fact, it's become second nature to ask, "What does ARTiE think?" in meetings—kind of like having a digital brain trust always on call. On the upskilling front, forget dusty training modules. EY's learning experience is all about real-time feedback, customizable coaching, and digital tools tailored to each consultant's career dreams. There's even a mandatory AI fluency program to help everyone, from new hires to old hands—stay ahead of the curve and turbocharge their client impact. The biggest culture shift is the rise of "human-AI teaming." At EY, consultants and algorithms don't compete, instead they team up. That means less grind, more collaboration, and (dare I say it?) more fun. With AI handling the grunt work, EY teams spend more time brainstorming, problem-solving, and building real, lasting value for outsmarting complex challenges and wowing clients, not just ticking boxes.
At Nerdigital, we closely follow how firms like EY are reimagining their workflows in the age of AI—not just to automate, but to amplify human capability. What's happening at EY is more than digital transformation; it's a shift in how teams think, collaborate, and grow. And I find it both inevitable and inspiring. One of the most profound shifts is in human-AI teaming. Instead of viewing AI as a tool that replaces analysts or consultants, EY is designing roles and workflows around collaboration with AI. Whether it's surfacing risk factors in real-time during audits or generating first-draft insights from large datasets, AI is acting like a cognitive co-pilot. This frees up consultants to focus on the higher-order thinking clients actually pay for—judgment, empathy, and strategic perspective. That kind of shift requires a massive cultural change, especially in how people learn. Learning and development at EY is no longer confined to static e-learning modules. We're seeing dynamic, AI-driven learning paths that adapt to each employee's role, gaps, and pace. The mindset is: "If your job is changing fast, your skills should too." AI is helping personalize that journey at scale. The way teams collaborate internally has also evolved. Digital platforms aren't just productivity dashboards anymore—they're intelligence layers. I've seen how EY integrates AI into platforms like Teams or proprietary dashboards, so team members don't have to chase data. Instead, context-aware insights and task nudges show up when and where they're needed. It keeps projects flowing more efficiently and reduces cognitive overload, especially on large, cross-functional teams. What impresses me most is how consultants are adapting their value proposition. At Nerdigital, we've worked with clients who now expect consultants to interpret AI outputs, not just gather data. EY is ahead of that curve. They're upskilling consultants to be strategic translators—people who understand both the tech and the business. That blend is rare and valuable. If there's a lesson in what EY is doing, it's that the future of work isn't man versus machine—it's about integration. The organizations that win will be the ones that embrace AI not to dehumanize work, but to double down on what makes people irreplaceable: insight, creativity, and trust.
AI is re-writing the job of consultants - less manual grunt work, more strategic thinking. The change that I have observed reflects the way engineering teams leverage AI tools to do debugging, prototyping and automate workflows. In companies such as EY, AI is not going to get rid of consultants, but rather transform them into systems architects. They are supposed to lead the clients through more and more complicated tech stacks, rather than create PowerPoint decks. The learning has transitioned into continuous calibration. AI driven feedback loops are currently being added to how consultants learn regulations, tax code, or risk models in a weekly up-skilling process. Just like the developers do it is train, test, iterate. Human-AI teaming is not poetry, it is practical: it takes NLP tools a few seconds to summarize a 400-page long contract and allow teams to advise at the velocity and depth they can. There is also a shift in the value delivery model. Clients are not interested in having answers, but they are interested in explainability. Consultants, however, are necessary there: they take all AI-derived insights and convert them into choices that could be used by stakeholders. And that is the new bar.
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Digital platforms have made our internal communication more fluid and less dependent on hierarchy. AI powered dashboards give everyone visibility into project status, upcoming deadlines and key performance metrics. This transparency reduces the need for constant status meetings and empowers teams to self manage effectively. It also fosters accountability by making progress visible to all stakeholders. The result is leaner more focused collaboration. On the learning side we have embraced AI driven peer learning platforms. These match consultants with others who have solved similar challenges in different industries. The exchange is enriched by AI's ability to surface supporting resources and best practices instantly. This expands knowledge beyond formal training into real world problem solving. Clients benefit from solutions shaped by both broad experience and specific and relevant insight.
At EY, it is not a matter of replacing but rather about approaching the way teams work as a unit in a different way. AI is transforming the cadence of internal cooperation. AI technologies are now used to run routine research, data pulls and formatting and remove this burden off consultants, allowing them to spend more time on decision-making and conversations with clients. The paradigm is shifting towards insight creation rather than task performance and that alters who you recruit, and how teams are constructed. Learning-wise, upskilling is no longer a thing that you plan. It occurs within the stream of work. Digital systems in EY now provide training prompts depending on the activity an individual is performing in real time. A consultant who is constructing a model will get prodded with short videos or hints specific to that particular task. This saves on the learning curve without removing people off projects. The larger change is the way that consultants conceptualize value. It was the matter of being more knowledgeable than the client. Now it is of assisting the client in interpreting the data that moves so fast and take action on it with certainty. Artificial intelligence would do the hard work but people still have judgment, timing, and nuance. The new edge is developing on that balance.
I've been coaching executives for 30+ years and watching AI transform leadership development firsthand. At Berman Leadership, we're seeing organizations struggle with the same challenge EY faces - how do you maintain human connection while leveraging digital efficiency? The most successful changes I've witnessed combine AI-powered personalization with human psychology. One hospitality client used our approach during COVID - they created 100+ digital learning assets that reached 430,000 associates in two months. But the key wasn't the technology - it was understanding that people still needed psychological safety and human connection during change. Here's what actually works: Use AI for the heavy lifting (data analysis, content delivery, scheduling) but double down on human coaches for the complex stuff - emotional intelligence, conflict resolution, strategic thinking. I'm seeing teams where AI handles routine check-ins and progress tracking, freeing up consultants to focus on high-stakes conversations and creative problem-solving. The consultants who thrive aren't being replaced by AI - they're becoming AI-augmented facilitators. They use real-time data insights to personalize their coaching approach, but they're still the ones reading body language, navigating office politics, and helping leaders through messy human challenges that algorithms can't touch.
I've seen the rise of AI and digital platforms at EY completely change how my team works and learns. It's not just about using fancy tools; it's about how those tools actually shape our thinking. I remember the first time I teamed up with an AI assistant on a client project. It handled the repetitive number-crunching in minutes, so I could focus on the real problems, like what the data meant and how we could use it to help the client make smarter choices. That shift made me feel more valuable, not less. What surprised me most was how learning has changed. Instead of waiting for training sessions, I've had to pick up new tools on the go, asking questions, trying things, sometimes failing fast. That kind of learning sticks. My advice is this: don't be afraid to explore tech even if it feels way out of your comfort zone. The more you treat AI as a teammate, not a threat, the more confident and creative you become. For me, it's not about replacing what I do; it's about making what I do matter more.
The rise of AI and digital platforms at EY has completely changed how I work with my team and clients. Internally, collaboration is faster—tools like EY Canvas and our AI-enabled knowledge systems help us tap into global expertise in real time. I recently worked on a project where our AI assistant summarized 100+ pages of regulatory updates overnight—something that would've taken me days. It didn't replace my work, but it sharpened my insights. For upskilling, EY's digital badges make it easy to learn while working. I've earned badges in data visualization and AI ethics—both directly applied to client engagements. What's changed most is the consultant's role. We're not just advisors now—we're AI translators, helping clients navigate tech without losing the human touch. Human-AI teaming isn't buzz anymore—it's real, and it's reshaping how we deliver outcomes.
Running Sundance Networks for 17+ years, I've watched AI transform how MSPs deliver value - but not in the way most people expect. The real revolution isn't replacing consultants; it's turning us into proactive problem-solvers instead of reactive firefighters. Our AI-powered monitoring now catches network issues before they crash client systems, which sounds basic until you realize this fundamentally changed our role. Instead of spending 60% of our time on emergency repairs, my team now spends that time on strategic planning and business growth initiatives with clients. We went from being the "fix it" guys to being growth partners. The upskilling challenge hit us hard when we launched our weekly AI briefings. My technicians had to learn to interpret AI insights and translate them into business language for CEOs who don't care about server logs. The guy who used to just swap out routers now walks into boardrooms explaining how predictive analytics can prevent costly downtime during their busy season. What surprised me most is how AI made our human expertise more valuable, not less. When our penetration testing partner's AI flags 200 potential vulnerabilities, clients need someone who understands their actual business risk - like knowing that the "critical" server vulnerability might be on a machine they're replacing next month anyway.
The use of AI has democratized access to sophisticated analytical tools across all levels of our teams. Even junior consultants can now run complex models and scenario planning exercises without specialist intervention. This broadens the base of contributors capable of influencing strategic outcomes. It also accelerates learning by immersing team members in advanced work early. The effect is a deeper, more capable talent pool across the organization. For learning and development, AI curates knowledge from across our global network into digestible, role-specific insights. This prevents information overload while keeping everyone aligned with the latest industry shifts. The focus on relevance ensures time spent learning has a direct business impact. It also fosters a culture of continuous curiosity. Clients engage with teams that are constantly informed and primed to deliver fresh perspectives.
AI and digital tools at firms like EY are rewriting the playbook. Teams aren't just crunching numbers—they're interpreting insights AI surfaces in seconds, which used to take hours. That means more time on strategy, less on spreadsheet gymnastics. L\&D is shifting too—upskilling now means learning how to *ask* better questions of AI, not just how to use the tools. Consultants are evolving from deliverable machines to problem framers and trust builders, working *with* AI instead of competing against it. It's less about having all the answers and more about guiding the client through the noise with the right ones.
As someone deeply involved in AI development, I've seen firsthand how EY's digital transformation is creating more efficient workflows through AI-assisted project management and automated task prioritization. In my experience leading Magic Hour, we've found that AI tools work best when they complement human creativity and decision-making, similar to how EY teams are using them for initial analysis while keeping strategic thinking human-led. The key has been focusing on upskilling teams to work alongside AI, not compete with it - like teaching consultants to prompt AI effectively while maintaining their industry expertise.