In the latest episode of The Learning Summit Podcast, Sean Gilligan, founder of Webanywhere, explores how multimodal learning and AI are transforming education. Platforms like Watch and Learn, Gemini, and NotebookLM are creating personalized, flexible, and engaging learning experiences by integrating text, audio, video, and live interaction.

“Multimodal learning supports different styles—whether you prefer listening, watching, or interacting live,” Sean explains. “It’s about offering flexibility while keeping learners engaged.”

Sean also highlights how AI enhances real-time engagement: “Imagine live quizzes and polls during a session, giving presenters instant feedback to adapt and meet learner needs on the spot.”

These advancements don’t just enhance engagement—they empower educators with insights to refine their content and strategies. “With tools like NotebookLM, learners can even revisit sessions, generate podcasts, and ask AI hosts questions, creating a truly adaptive learning journey,” Sean adds.

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Unlocking Learning Potential: Totara Learn, Engage, and Perform Features Explained

Alex (Host):

Hello, and welcome back to the Learning Summit Podcast! I’m Alex, and today’s episode is all about one of the most flexible, powerful learning platforms out there: Totara LMS.

Joining me is Sean Gilligan, founder of Webanywhere and an expert in learning technology solutions. Sean, welcome back!

Sean Gilligan:

Thanks, Alex. Always great to chat with you, and I’m excited to dive into Totara today. There’s so much happening with the platform—especially with the upcoming Totara 19 release.

Alex:

We’re going to unpack a lot here, but let’s start at the top. Sean, Totara offers three core products: Totara Learn, Totara Engage, and Totara Perform. What are they, and how do they work together?

Sean:

Good question, Alex. Totara is essentially a suite of tools built to manage learning, collaboration, and performance within organizations.

Totara Learn is the LMS side of things—focused on delivering formal training programs like onboarding, compliance training, and professional development.

Totara Engage takes things further by enabling social learning and collaboration—it’s all about peer-to-peer knowledge sharing, content curation, and driving engagement outside of traditional courses.

Totara Perform focuses on performance management, bringing goal-setting, competency tracking, appraisals, and continuous feedback into one platform.

Together, these tools cover everything from structured learning to informal collaboration and real-time performance tracking.

Alex:

So it’s a full ecosystem for learning and development. Let’s start with Totara Learn—the LMS that most people are familiar with. What makes it stand out?

Sean:

Totara Learn is incredibly flexible, which is its biggest advantage. You can tailor everything—from learning pathways to branding—to fit your organization’s needs.

With Totara Learn, you can:

•Create custom learning pathways for different roles or departments.

•Track and manage compliance training, ensuring everyone is up to date with required certifications.

•Integrate with external systems like HR tools or CRMs.

•Use detailed reporting to track learner progress and training ROI.

It’s ideal for organizations that need to deliver structured, formal learning at scale—whether that’s a global enterprise or a small team growing rapidly.

Alex:

It sounds robust and very adaptable. Now, you mentioned Totara Engage, which adds collaboration and social learning. What does that bring to the table?

Sean:

Totara Engage is all about making learning more collaborative and dynamic. Not everything an employee learns comes from a formal training course—people learn by sharing knowledge, reading articles, watching videos, and connecting with peers. Engage helps facilitate all of that.

Key features include:

• Content Curation: Employees can find, share, and curate resources—like videos, podcasts, and articles—to support their learning.

• Social Collaboration: You get tools like forums, discussions, and peer-to-peer feedback to create a real learning culture.

• Workspaces: Teams or projects can create dedicated spaces to share resources and collaborate on learning goals.

Alex:

So it’s great for organizations trying to promote continuous, informal learning alongside traditional training.

Sean:

Exactly! Engage helps organizations unlock the knowledge that already exists within their teams and puts it to good use.

Alex:

And then there’s Totara Perform—the performance management piece. How does that tie in?

Sean:

Totara Perform is all about connecting learning with employee performance. It helps organizations identify skill gaps, track progress, and align training with individual and business goals.

Some of the standout features include:

• Goal Setting: Managers can set performance goals that are tied directly to learning objectives.

• Competency Management: You can map learning outcomes to specific skills and competencies.

• Continuous Feedback: Employees and managers can track progress with regular check-ins and real-time feedback loops.

• Performance Reviews: It centralizes appraisals, making it easier to evaluate employees while aligning their development with company goals.

The benefit here is that performance management isn’t treated as a separate function. It becomes integrated with learning, so employees are constantly growing and contributing to the company’s success.

Alex:

That’s huge. So instead of annual performance reviews feeling like a chore, they’re part of an ongoing, dynamic process.

Sean:

Exactly! And it’s driven by real data from both learning progress and performance metrics.

Alex:

Now, something big is happening with Totara 19. Totara Learn and Totara Engage are being merged into one platform. Why is that such a significant update?

Sean:

This is a big deal, Alex. Traditionally, Learn handled formal training, while Engage handled informal learning and collaboration. By merging them into one platform, Totara 19 makes it seamless for organizations to combine structured learning with social and peer-driven experiences.

Imagine an employee completing a formal course in Totara Learn, but immediately sharing insights or related resources in a Totara Engage workspace. It’s a more integrated learning experience that reflects how people actually learn on the job.

For administrators, it simplifies things too—you don’t need to manage two separate systems. It’s one unified platform with a clean, user-friendly experience.

Alex:

It really seems like Totara is doubling down on the idea of blended learning—formal, informal, and performance management all in one ecosystem.

Sean:

That’s exactly it. Totara isn’t just a learning platform—it’s a complete solution for developing people. Whether you’re delivering compliance training, fostering collaboration, or improving employee performance, Totara brings it all together.

Alex:

If someone’s listening and thinking, “This sounds perfect for my organization,” what’s the best way to get started?

Sean:

The first step is to explore your goals. Are you focused on compliance? Do you want to foster social learning? Or are you looking to align learning with performance? Totara can handle all of it, but it helps to identify where you want to start.

At Webanywhere, we help organizations implement Totara, customize it to their needs, and train teams to make the most of it. You can visit webanywhere.com to set up a demo and see how Totara can transform your learning and performance strategy.

Alex:

Sean, this has been such a great conversation. Totara Learn, Engage, and Perform really offer a complete package for organizations that care about developing their people. And with Totara 19 merging Learn and Engage, it’s only getting better.

Sean:

Absolutely. Thanks for having me, Alex—I always enjoy talking about how technology can unlock learning potential.

Alex:

Thanks, Sean. And to our listeners, if you’re looking for a flexible, powerful solution to manage learning, collaboration, and performance, visit webanywhere.com to learn more about Totara LMS and how it can help your organization thrive.

Until next time—keep learning, keep growing!

The post What is Totara? appeared first on Webanywhere.

How to Train Your Staff on AI and Get the Most Out of Gemini, ChatGPT, and Microsoft Copilot

Training your staff on AI tools like Gemini, ChatGPT, and Microsoft Copilot isn’t about turning them into data scientists. It’s about showing them how these tools can make their work easier, faster, and better. It’s about shifting their mindset from “AI is confusing” to “AI saves me time.”

AI Isn’t Coming, It’s Already Here

We all get too many emails. We’ve all wasted time in meetings that could’ve been handled over Slack. The truth is, we’re drowning in busy work. AI can fix that, and it’s not as complicated as you might think. Whether it’s Gemini, ChatGPT, or Copilot, these tools are designed to get things done faster and with fewer mistakes.

You don’t have to be a tech wizard to use them either—what you need is curiosity and a willingness to learn. That’s the real magic of AI: it makes the hard stuff easy, once you know how to use it.

Use Cases That Change the Game

•ChatGPT for Creative Work: Say you’re writing a proposal, drafting an email, or brainstorming content ideas. ChatGPT can do the heavy lifting. It helps you structure your thoughts, check your tone, and even proofread. It doesn’t replace creativity; it just amplifies it. What used to take hours can now be done in minutes.

•Microsoft Copilot for Document Creation: Think about how much time your team spends on presentations, reports, or data analysis. Copilot is like having an extra set of hands in Microsoft Office. It can summarize documents, create slides, and even generate insights from spreadsheets. The mundane, time-consuming tasks disappear, and your team gets back hours to focus on strategy and execution.

•Gemini for Research and Deep Learning: When it comes to digging through information or gathering insights, Gemini’s chat-driven approach helps by cutting through the noise. Imagine asking Gemini to research industry trends or analyze complex data, then providing you with actionable insights in real-time. It’s like having an expert consultant available 24/7.

Rolling Out AI Training

1. Start Small, Go Wide: Don’t try to overwhelm everyone with every feature at once. Instead, pick one tool—maybe ChatGPT—and integrate it into a specific workflow like email drafting. Once people see the benefit, they’ll be more eager to try other tools. Start with the most time-consuming tasks that everyone can relate to.

2. Workshops Over Lectures: AI training isn’t a seminar, it’s hands-on. Have people bring real work problems to the table and solve them with AI during training sessions. Instead of theory, focus on practical application. How can Gemini help a marketing team? How can Copilot streamline finance reports? Make it relevant.

3. AI Champions: Identify a few early adopters within your team—people who naturally get excited about tech. Let them become your internal AI champions. They can answer questions, test new tools, and help train others. Peer learning always works better than top-down instruction.

4. Regular Check-ins: AI isn’t static. It evolves, and so will your team’s use of it. Host regular check-ins or “AI office hours” where anyone can drop in to troubleshoot, ask questions, or share tips. The goal is continuous learning, not one-and-done training.

Make AI a Habit, Not a Tool

The real benefit of AI tools like ChatGPT, Copilot, and Gemini comes when they become part of your team’s daily routine. It’s not about using AI just because it’s the new thing. It’s about embedding it into how you work. Over time, AI stops feeling like “tech” and starts feeling like the air you breathe—essential and invisible.

The result? Less time on repetitive tasks, fewer mistakes, and more time spent on meaningful, high-quality work. Isn’t that the goal for any business?

In the end, training your staff on AI isn’t just about teaching them how to use a tool. It’s about changing how they think about work. Once they see the power of AI to reduce time spent on the busy work and increase the quality of what they produce, there’s no going back.

AI is quickly becoming a part of the modern workplace, and it’s making a noticeable impact on how we allocate our time. The graph above visualizes this shift, showing how much time different roles can spend using AI versus sticking with traditional methods. It’s clear that AI isn’t just hype—it’s fundamentally changing how work gets done. But the shift isn’t equal across the board, and that’s where the real story lies.

Let’s take customer support and data entry, for example. These are roles that thrive on repetition, where AI can take on a lot of the heavy lifting. Chatbots, automated workflows, and document recognition systems are already doing the jobs that used to require manual effort. The result? More hours freed up to focus on tasks that require a human touch—like solving unique customer problems or handling more complex data analysis. In these jobs, AI is a game changer.

Now look at marketing and sales. AI isn’t replacing creativity, but it’s making the process smoother. Whether it’s audience targeting, content personalization, or automating reports, marketing teams are saving time with AI without sacrificing quality. Sales follow a similar trend—AI is handling the repetitive stuff like lead scoring and customer follow-ups, but the heart of sales—relationship building and closing deals—remains human-driven. In these roles, AI enhances efficiency without taking over.

In accounting, automation is eating up mundane tasks like invoice processing and basic financial analysis, leaving accountants to focus on more strategic, high-value work. The numbers tell the story: AI isn’t replacing accountants, but it’s certainly reducing the hours they spend on manual tasks. This allows teams to shift from transactional work to advisory roles, providing insights and strategy that drive business value.

Software development is another field where AI is starting to make an impact, but not in the way some might expect. Developers are using AI for tasks like code generation, bug detection, and even testing. Yet, the creative and problem-solving aspects of development remain firmly in human hands. AI is here to help, but it’s not writing your next app by itself.

Project management might be one of the slower adopters, but it’s starting to catch up. Tools that automate workflows, scheduling, and reporting are streamlining the more tedious parts of the job. But project managers aren’t going anywhere—there’s still a big need for human decision-making, leadership, and strategy. AI is just another tool in the toolkit, not a replacement.

The evidence backing up these estimates comes from various studies and trends we’re seeing across industries. McKinsey and PwC reports show that automation is already cutting down time in customer service, admin, and accounting roles. Meanwhile, tools like Salesforce’s Einstein and HubSpot are proving that AI can deliver real results in marketing and sales. And while software development teams are increasingly using AI to automate parts of their workflow, experts agree that it will complement developers rather than replace them.

Totara is bringing AI into the world of learning management systems (LMS) in a way that changes how organizations approach training and development. AI in Totara enhances learning personalization by analyzing learner behavior and tailoring content to their needs. It’s not just about recommending courses—AI can identify skills gaps, suggest development paths, and even track progress more intelligently. This kind of adaptive learning keeps users engaged by delivering the right content at the right time, improving both the quality and effectiveness of training. It’s about using AI to not only teach better but to help learners learn smarter.

Sound Branch is taking a different but equally exciting approach, making AI central to how people interact with voice notes. By using AI to transcribe and summarize audio recordings, Sound Branch turns spoken word into text, making voice communication more versatile. This allows users to capture ideas verbally and have AI generate concise summaries or searchable transcripts, saving time and improving accessibility. It’s not just a voice platform anymore—it’s a multimodal tool that combines audio with text, making it more social and interactive. The ability to quickly skim, share, and respond to transcribed conversations keeps discussions alive long after the recording stops, pushing collaboration to new heights.

In the end, AI’s role in the workplace is about balance. It’s not about replacing humans—it’s about freeing them up to focus on the parts of their job that truly require creativity, problem-solving, and human interaction. The key takeaway is simple: AI is here to stay, but it’s not going to work for you unless you train your team to use it effectively. When you do, the payoff is undeniable—less time spent on the mundane, and more time spent on work that matters.

Sources

McKinsey AI Report on Customer Service

PwC AI Automation Report

Gartner Forecast for AI in Software Development

McKinsey AI in Project Management

The post How to Get Your Staff Engaged with AI appeared first on Webanywhere.

Imagine a scenario: a large organization relies on its L&D department to design and deliver training, manage an LMS, create content, and measure success through assessments and analytics. Traditionally, these tasks required a significant investment of time, often split between designing learning programs, developing content, providing learner support, and running assessments. Now, with AI in the mix, that time equation is shifting.

Take instructional design, for example. AI can now provide frameworks, templates, and initial drafts for learning materials. Instead of spending 20 hours per week meticulously crafting each course, instructional designers may only need 15 hours to refine what AI has already started. The process becomes about curating rather than creating from scratch. Content development, long a time-consuming task, is reduced even more dramatically. Where once professionals might spend 15 hours per week writing content, they may now spend just 5, with AI generating initial drafts and outlines. The work becomes about fine-tuning, personalizing, and ensuring the tone is right.

Conversely, areas like learning analytics are expanding. AI is providing more data than ever before, but interpreting this data—translating it into actionable insights—requires human intuition and expertise. Time spent in learning analytics will increase, with professionals now needing to focus on what the data means for the organization’s strategy and long-term goals.

Current Time Spent Per Job Type in L&D (Pre-AI)

Projected Time Spent Per Job Type in L&D (Post-AI Adoption)

Similarly, L&D leaders will need to spend more time on planning and strategy. AI can generate mountains of data and automate routine tasks, but human insight is critical for connecting those dots. What is the future of learning in this organization? How do we use AI’s insights to shape long-term strategies? As AI frees up time elsewhere, this becomes the crux of the L&D professional’s role—translating machine-driven insights into human-centered outcomes.

So what does this mean for the future of L&D professionals? It’s simple: adapt or fall behind. As AI handles the more repetitive aspects of content creation, coordination, and assessment, L&D professionals need to shift their focus. The future is about data interpretation, strategic thinking, and human-centered leadership.

Before AI: Traditional L&D Process Flow

1. Needs Analysis
[L&D Team] –> Conduct manual surveys, interviews, and feedback analysis

2. Program Design
[L&D Team] –> Manual design of learning objectives and curriculum

3. Content Creation
[L&D Team] –> Develop training materials, presentations, and courses from scratch

4. Training Delivery
[Instructor-Led Training] –> In-person or virtual sessions, mostly standardized

5. Assessment & Evaluation
[L&D Team] –> Collect feedback, conduct manual assessments/tests

6. Reporting & Improvement
[L&D Team] –> Analyze data manually and make adjustments for future programs

After AI: AI-Enhanced L&D Process Flow

1. Needs Analysis
[AI-Powered Analytics] –> Automated analysis of performance data and skill gaps
↓
[L&D Team] –> Interpret insights and align business goals

2. Program Design
[AI Recommendations] –> AI suggests learning paths and training objectives based on data
↓
[L&D Team] –> Validate and adjust program design

3. Content Creation
[AI-Generated Content] –> AI creates customized training modules, quizzes, and learning materials
↓
[L&D Team] –> Curate and refine AI-generated content

4. Training Delivery
[AI Chatbots & Virtual Tutors] –> AI delivers personalized learning through chatbots and virtual platforms
↓
[L&D Team] –> Focus on coaching and handling complex queries

5. Assessment & Evaluation
[AI-Based Adaptive Assessments] –> Real-time assessments with instant feedback loops
↓
[L&D Team] –> Monitor AI-generated insights and learner progress

6. Reporting & Improvement
[AI Predictive Analytics] –> Continuous feedback and predictive data to optimize learning
↓
[L&D Team] –> Proactively adjust learning strategies

Imagine the L&D department as a finely tuned orchestra. In the past, each musician—the L&D team—was responsible for not only playing the instruments but also writing the sheet music, setting the tempo, and even analyzing the acoustics of the room. Every step, from data collection to content creation, was laborious and manual, leaving little room for the big picture. Enter AI, and the entire dynamic shifts. Automation steps in, taking over the tedious tasks like data collection and content generation. Personalization now happens in real-time, with AI crafting tailored learning paths and adaptive assessments for each individual. As a result, the L&D team is liberated from the minutiae, their focus now on strategy, validation, and guiding the larger, more complex conversations. It’s a transformation, where the orchestra still plays, but the conductor now has the freedom to lead with creativity and precision, rather than getting lost in the mechanics of the music.

What Skills Should L&D Professionals Focus On?

1. Data Literacy: With AI generating more learning data than ever before, L&D professionals need to become fluent in interpreting this data. The ability to derive actionable insights from complex data sets will be invaluable. This isn’t just about understanding what the numbers say, but also what they mean for learner success, engagement, and future strategy.
2. Strategic Thinking: As routine tasks become automated, L&D professionals will need to think more like business leaders. The ability to align learning initiatives with organizational goals, forecast future needs, and adjust strategies based on data insights will become key to thriving in an AI-enhanced environment.
3. Emotional Intelligence: AI may be able to create learning content, but it cannot replace the human touch. Understanding learners’ needs, building rapport, and fostering an inclusive learning culture will remain critical. Professionals who excel in these areas will be the ones who guide their teams through the AI transformation, ensuring that the human side of learning doesn’t get lost in the technological shuffle.
4. Continuous Learning: In an AI-driven world, the pace of change is relentless. L&D professionals must continuously update their skills, not only in technology but in leadership, strategy, and the softer skills that AI cannot replicate. Staying curious and committed to learning will be essential.
5. Creativity and Problem Solving: While AI can handle tasks like generating content or analyzing data, it lacks the creativity and innovation that humans bring to problem-solving. L&D professionals should focus on creative ways to use AI tools, enhance learner experiences, and design new learning solutions that go beyond what the algorithms can generate.

The bottom line is that AI will change the way L&D professionals work—but it won’t replace them. The skills that machines can’t replicate—insight, empathy, strategic thinking, and creativity—are the ones that will matter most in the AI-enhanced L&D landscape. Those who embrace this shift and adapt their skill sets accordingly will thrive. The rest may find themselves left behind in a world that is moving forward at an unprecedented pace.

In this new era, AI isn’t the end of human-driven L&D—it’s the beginning of a new kind of partnership between humans and machines. And the future of learning will be defined not by the technology itself, but by those who know how to harness it.

The post How AI is Redefining Roles and Skills in L&D appeared first on Webanywhere.

Take, for instance, the new voice mode introduced with ChatGPT’s latest models. It’s not merely a feature; it’s a reimagining of how we interact with information. You speak, the AI listens, and what follows is a dialogue, not a monologue. You can interrupt, question, and redirect the conversation. Gone are the days of waiting for lengthy responses or struggling with unclear instructions. The responsiveness, the back-and-forth nature, mimics human conversation but with the precision and speed of a machine. This makes the process of learning not only faster but more intuitive. It feels less like a session with a tutor and more like a conversation with a well-versed colleague.

Now, think about the implications for translators, coaches, and educators. Traditionally, these roles have relied on human expertise—empathy, nuance, and adaptability. But AI has begun to step into this space, not as a replacement, but as an enhancement. A translator powered by AI doesn’t just convert languages; it understands context, tone, and culture, offering near-instantaneous translations with accuracy that was unimaginable just a few years ago. Similarly, a coach using AI can provide feedback tailored to a learner’s unique pace, strengths, and weaknesses in real time. It’s personalized learning at a scale never before possible.

The efficiency gains are clear. Imagine an organization rolling out a global training program. Instead of hiring a cadre of trainers, an AI could lead those sessions, translating materials into multiple languages on the fly, answering questions instantly, and adapting the delivery to the needs of each learner. This isn’t a dream of the future; it’s happening now. And with these advancements, the role of the trainer shifts. Trainers are no longer the sole gatekeepers of knowledge but become facilitators of AI-driven learning experiences.

But efficiency isn’t the only outcome. There’s also the profound impact on the learning experience itself. Traditional models of education have long been criticized for their rigidity. Everyone learns at a different pace, yet we’ve often applied a one-size-fits-all approach. With AI, this is no longer necessary. Learners can move at their own pace, revisit materials as needed, and engage with the AI in ways that cater to their individual learning styles. This transforms learning from a passive activity into an active, dynamic engagement.

Still, these advancements raise important questions about the future of work. If AI can deliver personalized training, offer instant translations, and serve as a coach, what happens to the roles traditionally filled by people? For learning and development professionals, this means a shift in focus. The value will no longer be in the delivery of content but in curating, designing, and optimizing the learning experience. The human touch will still be needed, but it will be less about the act of teaching and more about understanding how people learn best—and how to use AI to facilitate that.

AI is not here to replace jobs; it’s here to change them. The demand for empathy, creativity, and strategic thinking will grow as routine tasks are automated. Trainers, educators, and coaches will become experience designers, tasked with crafting learning journeys that integrate both human and machine expertise. Those who embrace these tools will find themselves not diminished, but empowered.

We are at the cusp of a new era in learning and development. The advancements in AI, from voice interaction to real-time translation, are not just technological milestones—they are changing the way we think about education and work. And as these tools become more integrated into our daily lives, they will redefine what it means to learn, teach, and grow in ways we are only beginning to understand.

The post ChatGPT: Transforming Education and Jobs in L&D appeared first on Webanywhere.

How Is AI Changing The Way We Work?

From small changes such as email inbox filtering and email auto replies to AI assistants, the positive impact of technology in the workplace is plain to see. From the start of the employment process AI is heavily involved, from screening CV’s and increasingly popular use of skill games to assess the cognitive and emotional behaviour of candidates. Once in the workplace the implementation of AI processes and automation of mundane jobs enables employees to focus their time and energy on completing more complicated tasks to a higher standard as AI frees up employee time. The ways in which AI can grow and be implemented shows a lot of promise, such as CRM systems that learn from sales history, and guides employees on where to focus their sales energy to work more productively based on their work habits and past performance.

How Can AI Be Used In Employee Training?

Learning and development (L&D) is one of the key areas that AI is being implemented in workplaces across the globe, and also one that will see great advancements over the coming years. But, how can employees utilise training AI and what are the benefits of doing so?

Content Curation

As mentioned in our previous post, Learning and Development: Why Is Employee Development Important, curating a L&D strategy is vital. Thankfully, AI is on hand to help with this by taking into account the company objectives, the employees role and the training course. Once this has all been taken into account AI can curate custom training content in order to get the most out of the course and trainee.

Reinforcement

In order to make the most of L&D newly learned skills should be reinforced on an ongoing basis, however this is an area where training is often lacking. Once a training course is completed we tend to see this as ticked off, yet it’s a process that takes time. This is where AI can make a real difference; using it’s learned behaviours and reminder style systems it regularly reinforces the information we have just been taught to ensure this is really understood and taken on board.

Measurement

Large data sets are often quite unwieldy and time consuming to sort into manageable, and readable, results. Data such as employee training courses, employee surveys and employee reviews can easily be digested by AI and given back to us as tangible information we can use to help employees by skill matching for mentorships, on the job training or progression support. This use of AI frees up time by taking the heavy lifting of data sets off employers shoulders, and freeing up time for them to focus on the results and how to make positive changes off the back of them.

How do you see AI changing the landscape of the workplace in the future?[/vc_column_text][/vc_column][/vc_row]

The post Learning And Development: The Role Of AI In The Workplace appeared first on Webanywhere.

• Planning
• Reasoning
• Problem solving
• Knowledge representation
• Perception
• Motion
• Manipulation
• Social intelligence and creativity

It’s estimated that 1.5 million people in England are at risk of losing their jobs due to artificial intelligence and automation.

The office of National statistics says that 70% of roles that are at high risk, are currently held by women.

The Graph above supports the recent report by ONS which showed that employees in the food industry will be hit the hardest. After that, it could be workers in retail and then after that, teachers and medical practitioners.

There’s the question as to whether E-learning will take teachers jobs. Online courses are becoming important in many countries as they allows students to gain access to a greater depth of information than a teacher may be able to provide.

Robots and AI have started to worm their way into the retail industry. The majority of supermarkets now offer self service and more recently, departments and clothing stores now do.

Retail giant, Zara now offers self checkouts in some of their stores where you can buy or return items. Who needs a cashier anyway? In some HSBC banks, customers are greeted by a robot who questions why you might be there and if he can do anything to help. However, although this might seem that the robot has taken someone’s job, HSBC says that the reason behind it is so that it frees up bankers and specialised employees.

A survey by Pew Research Internet finds Americans are roughly twice as likely to express worry (72%) than enthusiasm (33%) about a future in which robots and computers are capable of doing many jobs that are currently done by humans. A survey was conducted where it showed that 46 countries and 800 working environments found that number of people forced out of jobs by machines could near the one billion mark by 2030.

It’s argued that jobs may be shredded, but not eliminated. Rather than worrying about jobs, bosses, employees and company, owners should introduce AI into the workplace rather than it be a threat.

The overall threat of AI is that it won’t only take away jobs but change what workers do. An example is before airlines and aeroplanes were created, we never would have dreamed of having a job as an air hostess. Or, before Apple was created, who knew what a tech genius was? So, despite forcing tens of millions out of jobs in the next four years, the WEF thinks near twice as many more job opportunities will be created.

Technology has affected our life both positively and negatively. New technology takes our lives to a different level. It might ruin jobs but we can’t forget about the jobs that are created due to technology.

A.I assisted health care technician is where doctors will need the same health care skills but also up to date technology to deliver them remotely, but using telemedicine tools and in-home testing equipment. Thanks to A.I nurses will also be able to diagnose and treat more ailments, leaving doctors to support these technicians and handle the trickier cases directly.

For example, if the health care sector hires a doctor to answer appointed Facetime calls people are more likely to seek medical advice if they have access to Facetime. This is because the citizens who work 9-5 may not have a chance to go see a GP but if they’re on their lunch break they will not need to leave work or take it off sick.

We have all tried Uber at least once, just from a little persuasion of ‘sign up now and receive £10 off’. Uber is classed as technology, rather than a taxi because it becomes safer and easier for users. This technology has created over two million jobs worldwide. Although, we had taxi drivers ten years ago and a lot of them will have changed jobs, Uber has created delivery services for companies such as Mcdonald’s with Uber Eats. All through an app, thanks to technology we now could not imagine life without them.

Social media has several roles which have been formed – ten years ago most people didn’t even know what social media was and now in the 21st century we couldn’t even cope with Facebook being down for 24 hours.

Social media platforms have been growing and developing ever since Facebook came out, it has become a key method in reaching a wide audience, as has Twitter, Instagram, and Snapchat. Instagram influencers with up to 1 million followers can receive around a six-figure salary.
There are now so many new job roles such as App Developers, YouTube Content Creators, even websites such as Airbnb has formed dramatically due to technology.

One main issue with these new jobs is they appeal to a much younger generation. It tends to be the employee’s losing jobs due to technology are the older generation. When we think back to coal miners, it took up so many jobs that when the demand was no longer needed, in the 70s so many were out of jobs because we had electric fires now.

It’s easy to blame technology for taking jobs but the reality is, we can’t live without it and it will continue to dominate our lives.

For more information on how AI could help your business contact Webanywhere.
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