AI skills in the workplace. Why do so few of us use the power of this technology?
AI is revolutionising the workplace, enabling businesses to work smarter and faster.
Despite its increasing powerful, its potential remains untapped. Through my strategy work, I have noticed three primary barriers preventing organisations from capitalising on the advantages it offers.
- a lack of awareness about AI’s power
- a fear of technology as a replacement for people
- a lack of resources to invest in AI solutions.
The truth is that deploying AI solutions can help us gain efficiency and improve productivity, allowing us to stay ahead in today’s competitive world. See this weeks feature article for an interesting perspective on AI skills in the workplace.
The 3 faces of digital transformation
To deliver digital transformation requires a coordinated approach across many parts of an organization. This is proving to be difficult and is creating a great deal of tension, push-back, and disappointment.
Do your digital strategy meetings remind you more of an experiment in Brownian Motion rather than a managed conversation aimed at structured decision making? You’re not alone. The levels of frustration and tension across teams are on the rise.
When I talk with teams about barriers to progress, they quickly highlight the lack of cohesion, often expressed as absence of “a joined up conversation”. Much of the time, discussions about digital transformation devolve into several different conversations taking place at the same time. It is perhaps the one complaint I hear more now than ever before.
I was in this position myself recently and for a long time was scratching my head trying to figure it out. In a room full of intelligent, passionate people wanting to advance adoption of digital approaches to better meet the clients’ needs, the discussions bounced around from one topic to the next. The more I focused, the less I seemed to be able to follow what was going on. People were talking at each other rather than interacting to share ideas.
What are the 4 different types of blockchain technology?
Public, private, hybrid or consortium, each blockchain network has distinct pluses and minuses that largely drive its ideal uses — and will determine which one is best for you.
According to Gartner, enterprise production use cases are expected to grow by double-digit percentages in 2021. However, different use cases require different types of blockchain.
There are four main types of blockchain networks: public blockchains, private blockchains, consortium blockchains and hybrid blockchains. Each one of these platforms has its benefits, drawbacks and ideal uses.
The Future of Data is Real-Time
If your organization is already feeling pressure to deliver analytics faster and faster to support real-time use cases, be prepared for that pressure to only increase over time.
I honestly don’t know how I fed myself, found my way home, hailed a taxi to important meetings or discovered what my friends were up to 15 years ago. Today, we rely on having apps like DoorDash, Waze, Uber or Social Media at our fingertips, and depend on them being accurate and timely – often with less than a minute’s tolerance for any delays.
While these sophisticated companies have figured out how to deliver real-time apps, for you this is bad news if you’re in the business of delivering software experiences to customers or staff. User expectations for data freshness and accuracy are already externally set by their experiences as consumers.
If your data architecture uses batch ETL concepts from 15 years ago, your users will feel it and – more alarmingly – you’re at risk of losing them to competitors with a modern data stack that delivers streaming, real-time data. In today’s environment where everyone is a savvy consumer of tech experiences, your user experience is a big part of your brand.
Microsoft wants generative AI to be a copilot for enterprise applications
The goal at Microsoft is to help organizations benefit from the power of generative AI in an approach that is easy to consume and extend.
Microsoft is doubling down on its generative AI efforts, announcing today that it is integrating the technology into its Microsoft Dynamics and Power platforms. The goal is to enable enterprise applications with the power of generative AI.
Microsoft has been steadily integrating AI into its portfolio in recent years, thanks in part to the company’s expansive partnership with generative AI vendor OpenAI. For developers, Microsoft has already built the GitHub Copilot service which benefits from OpenAI’s Codex model to act as a pair programmer. Now Microsoft is extending the copilot model and bringing it to its enterprise applications beginning with Microsoft Dynamics 365 suite.
The new Microsoft Dynamics 365 Copilot service brings a range of capabilities to help automate business application operations for customer relationship management (CRM) as well as enterprise resource planning (ERP). The capabilities include text generation, sentiment analysis and workflow automation to help make it easier for Dynamics 365 users to complete tasks quickly and accurately.
What is Google AI Bard?
Google responds to OpenAI’s ChatGPT with their own AI chatbot, Google Bard.
As everybody was going mad about ChatGPT, out of nowhere – Google released their very own experimental AI-powered chatbot – Google Bard. You could see that the competition was heavy, and Google needed a response. But was it a response to ChatGPT, or was Google Bard in the making?
The Big Reveal: Google AI Bard
So now we know that Google Bard is Google’s response to OpenAI’s ChatGPT. Let’s learn more about it. It has the same main quality – it is an artificial intelligence chatbot. It is able to respond to different queries in a conversational manner.
It uses information from the web, to provide high-quality responses that are up-to-date and easy for the user to understand. Google Bard uses a combination of machine learning and Natural Language Processing (NLP) to provide these high-quality yet realistic responses to the user.
AI Skills. Only 1 In 10 Uses Its Power At Work. Bosses Want To Change That.
In a Salesforce survey of 11,000 global workers, few said their day-to-day role currently involves artificial intelligence. But with the rise of technologies like ChatGPT and a focus on boosting workers’ skills, that’s shifting quickly.
When Minneapolis-based Tony Nguyen lost his job as a manager at a sandwich shop during the pandemic, he decided his next move was to jump into tech. After spending his first five years after college in the restaurant industry, Nguyen wanted to learn new skills like process automation and data analysis.
To help, Nguyen turned to Trailhead, Salesforce’s training and workforce development platform, where he earned certifications, completed programs and eventually landed a job as an administrator managing data and analytics for Salesforce products.
“Growing up I loved playing video games and with computers—it’s always been a passion,” Nguyen says. The next skill Nguyen wants to learn? Generative AI.
In a global survey of 11,000 workers conducted by Salesforce, only one in 10 employees said their day-to-day role currently involves artificial intelligence. But with the rise in technologies like OpenAI’s ChatGPT, the shift to skills-based hiring and an increasing focus on improving existing workforces amid the threat of a downturn, 80% of senior IT leaders cited a need to recruit and upskill employees in generative AI.
THE DIGITAL EYE
I hope these articles are valuable.
I am passionate about technology, and I want to share that passion with you. I believe that it’s essential for everyone to stay up-to-date on the latest trends, so I’ve set out to cover all aspects of the industry – from data analytics to blockchain and AI.
Please let me know if you want to see any other topics covered, and I would appreciate your help sharing this blog with others interested.