AI-BASED SCHEDULING IN SAP FIELD SERVICE MANAGEMENT

AI-based scheduling optimization is a topic that many maintenance and service organizations depend on to optimize their operations, increase their productivity, and customer satisfaction. So, how exactly do we make use AI-Based Scheduling and what are the benefits? SAP Field Service Management (FSM) optimizes schedules by using advanced algorithms to analyze vast amounts of data and variables, such as job priority, technician skill sets, location, availability, and customer preferences. This technology enables automated decision-making, ensuring the right technician is dispatched to the right job at the right time, and prioritizing urgent tasks to minimize downtime and deliver maintenance/service precision. By automating the scheduling process, AI reduces the risk of human error, enhances operational efficiency, and increases productivity by allowing field service teams to complete more jobs in less time. Moreover, AI-based scheduling can also make use of predictive traffic routing functionality, to ensure that resources are utilized effectively, reducing unnecessary travel time and fuel emissions/costs. In the remainder of this blog, we will discuss some of the key features that bring our AI-based scheduling solution to life. Automated scheduling Fully automated scheduling in SAP Field Service Management is a game changer for businesses looking to streamline their field service operations. With the ability to define triggers for automated scheduling on predefined periods, companies can ensure that their resources are being utilized to their fullest potential. This means that tasks can be automatically assigned to the most appropriate field technician based on factors such as skill level, location, and availability. Additionally, the system can take into account customer preferences and SLAs, ensuring that service appointments are scheduled at the optimal time for both the customer and the technician. With automated scheduling, businesses can quickly adapt to changes in demand and respond to urgent requests with ease. By reducing the need for manual intervention, errors and delays are minimized, allowing for faster response times and increased customer satisfaction. Customers can also define specifics to how the work is scheduled - i.e. it automatically released, how is the technician or customer notififed, are certain checklists automatically linked, and so on. Best technician matching Many customers also leverage “assisted planning” using our best matching technician algorithms. The best matching technician algorithm uses advanced analytics and artificial intelligence to optimize technician dispatch and scheduling. This algorithm considers factors such as technician skills, availability, job proximity, and service level agreements (SLAs) to determine the best match for a service request. In addition, the algorithm is highly adaptable and can be customized to suit the specific needs of different industries and maintenance/service types. This scenario is particularly useful when a dispatcher needs to make a quick decision, and can use the system to assist in the decision making.

HOW TO NAVIGATE DATA PRIVACY LAWS WHILE ELEVATING CONSUMER CONNECTIONS

Steffen Schebesta, an Entrepreneurs' Organization (EO) member in Toronto, is chairman of the board and VP of corporate development at Brevo, an intuitive, all-in-one marketing solution for small businesses. We asked Steffen how businesses can capitalize on new data privacy laws to build consumer trust in their company. Here's what he shared: As consumers continue to advocate for stronger data privacy rights, the trend is gaining traction worldwide. As we move forward in 2024, navigating new laws in the U.S. and stricter surveillance in the E.U. is critical. However, when you run a business, complying with these regulations isn't just about avoiding fines -- it's an opportunity to build trust with consumers through more transparent relationships. Recap of Data Privacy Changes in 2023 Last year, California, Utah, Virginia, Colorado, and Connecticut rolled out or amended data privacy laws. These laws, such as the California Privacy Rights Act (CPRA) and Virginia's Consumer Data Protection Act (VCDPA), aim to strengthen consumer rights and impose stricter obligations on businesses regarding data collection, usage, and storage. The CPRA, an amendment to the California Consumer Privacy Act (CCPA) of 2018, introduced key provisions, including notice requirements, opt-out rights, access and deletion rights, and data minimization principles. Similarly, VCDPA focused on obtaining consumer consent for sensitive data collection and providing opt-out choices. What this taught us was that we need to let customers have a say in what data they share and how they share it. Third-party data is a thing of the past. Zero-party data -- data that customers provide voluntarily, often in exchange for a benefit, as with email signup forms and preference centers -- allows consumers to communicate their expectations with you. In short: When asking for consumer data, be transparent and give them control. The Outlook for Data Privacy Regulations As we look ahead, there are several trends that will reshape business practices and marketing strategies: Continued enforcement of privacy regulations: Past violations of the E.U.'s General Data Protection Regulation (GDPR) have led to hefty fines. Non-compliance is not taken lightly in the E.U. Companies worldwide must comply when handling European citizens' data. Expect enforcement efforts to intensify and severe consequences for mishandling data. Increased focus on children's privacy: Recent hearings in the U.S. and past GDPR fines for mishandling children's data highlight the need for protecting minors. Legislative measures dedicated to safeguarding children's privacy are gaining traction, reflecting growing concerns about online safety. AI policy and transparency: Artificial intelligence brings forth new challenges for data privacy as AI processes personal data. Expect calls for greater transparency in data collection and usage to mitigate privacy risks. Consumer awareness and rights: Consumers are becoming more privacy-conscious and more aware of their data rights. Businesses should anticipate increased awareness and demands for privacy rights from consumers and be prepared to adjust their strategies accordingly. State-level privacy laws: Several U.S. states are set to introduce or amend privacy laws in 2024, each with its own set of requirements and implications for businesses: California's Delete Act: Effective January 1, 2024, this legislation empowers Californians to control their data held by data brokers. Users can request to remove their browsing history, purchase records, and inferred personality traits derived from digital behavior. Oregon Consumer Privacy Act (OCPA): Effective July 1, 2024, OCPA grants rights similar to the CCPA, including the ability to opt out of data sales and review personal information used in automated decision-making. Texas Data Privacy and Security Act (TDPSA): Effective July 1, 2024, TDPSA applies to businesses with significant revenue or handling data of Texas residents, emphasizing data security measures to protect sensitive information. Delaware Personal Data Privacy Act (DDPA): Effective March 26, 2024, DDPA provides rights akin to the CCPA, reinforcing the importance of transparency and consumer control over personal data. Montana Consumer Data Privacy Act (MTCDPA): Effective October 1, 2024, MTCDPA grants consumers access, deletion, and correction rights akin to the CCPA, further solidifying individuals' control over their personal information. New laws will continue to emerge, affecting business models and practices in the coming year. Business leaders must work proactively to comply with stricter data privacy requirements and set the benchmark for responsible data management. Takeaways for Business Leaders Data privacy laws will continue to redefine the relationship between businesses and consumers and play an increasingly important role in business practices. In the coming year, companies should proactively follow the latest legislation. By being proactive and transparent in how and why they use consumer data, companies can turn a difficult topic into a chance to foster customer trust. To trust businesses, users need control over their data and to understand what the data is collected for and why. Informing customers of how their data will be used is also an opportunity for companies to lay out a purpose for more data collection down the road, especially when the exchange offers a shared benefit for both parties, such as providing a more personalized user experience. Finally, it's important to move away from third-party data. Third-party channels are prone to manipulation and monetization, which could lead to someone else controlling your customers' data. Instead, businesses should prioritize zero and first-party data collection through open and owned channels. Direct and transparent data collection allows businesses to actually own their data, its distribution, and communications. It also provides better insight into customer preferences and is essential for following new regulations. Following these regulations will not only keep your business safe but also provide the opportunity to build customer relationships on a whole new level. EXPERT OPINION BY ENTREPRENEURS' ORGANIZATION @ENTREPRENEURORG

THE iPHONE MAKER MAY SEEM A LITTLE LATE TO THE AI PARTY, BUT THAT IS TYPICAL APPLE STRATEGY

As AI becomes part of nearly every tech headline right now, Apple faces increased criticism that it's late to the game. CEO Tim Cook even faced questions on the matter at Apple's most recent earnings call, and uncharacteristically hinted at Apple's future plans when responding to an analyst's question. Cook said Apple had long been working on AI tech and noted he was "excited to share the details of our ongoing work in that space later this year." For Apple watchers, that was a giant hint that the company is bringing AI to the forefront of its products. That supposition got some serious support with a fresh rumor that Apple was entering into some form of partnership with Google to leverage its Gemini AI product. If Apple goes all-in on AI, that will dramatically overhaul many people's online experiences, and change many businesses too. According to a recent Bloomberg report, Apple is currently amid "active negotiations" with Google. The deal, if it's reached, would license some of Gemini's features to power certain AI features in the new versions of Apple's iPhone and iPad software later this year, Apparently Apple is looking to bolster its image and text-based AI generation capabilities as quickly as it can. Google's Gemini AI system has been touted for its "multimodal" powers, meaning it can accept and also produce both text-based and image-based information. Multimodal AIs are more useful than simple text-based chatbots because one app allows the user to prompt the AI with, say, favorite colors and or example images and text to get it to, for example, dream up a new logo for your company. Though the image-producing part of Gemini did recently get Google into ethical trouble, it's likely just a wrinkle. A deal with Google to provide key aspects of the iPhone experience is also not unprecedented: Since the iPhone launched, Google had a deal with Apple to be its featured internet search provider in a partnership said to cost Google $18 billion a year. Demonstrating the extent to which Apple is leaping into the AI game, reports earlier this year said it had also quietly purchased a Canadian AI startup called DarwinAI, known for its efforts to make AI systems smaller and faster. This news tracks with Apple's overall user-privacy-centric ethos. Apple's priority of keeping AI systems operating on-device, rather than in the cloud -- as many other AIs do, including Google's -- may allow Apple to keep users' AI data more under their own control. By keeping it safely locked inside their phones' chips rather than running on a server far away, it creates a fundamental difference, very much in line with Apple's privacy sensibility. It's also been reported that Apple has been working on its own multimodal large language AI models, the same general style as Google Gemini. The company recently revealed details on its so-called "MM1" AI system, including insights into exactly how these models work. This isn't necessarily a sign Apple is embracing open source for its overall AI effort, however. It's merely an academic paper produced to share insights with other researchers into novel AI systems, which is fairly common practice. Add the Google deal, its purchase of DarwinAI, and the MM1 research news together and it paints a very clear picture: Apple is going big on AI this year. Though Apple has been criticized for being "late" to the AI game, it has actually been working on AI for years -- the entire Apple designed and made range of chips powering its mobile devices and Mac computers contain dedicated sections for processing machine learning, the math algorithms that underpin lots of AI models. Apple tends not to enter a market until it has done its own background work, then swooping in with a cutting-edge offering, the recent Vision Pro launch being an excellent example. It's possible to make a few informed guesses about how this move will impact the millions of developers that write Apple apps, as well as the many business users of Apple systems. Developers keen to seize the zeitgeist and leverage AI systems into their apps may find Apple directly supporting their coding efforts with dedicated AI API features -- little fragments of code that let app writers hook up directly to Apple's special systems. Meanwhile, business users of iPhones and perhaps Macs will find their systems mirror rival AI efforts, with more business-enabling intelligence embedded into software and hardware. That's a parallel to Microsoft's efforts, of course, with the PC software maker even pushing to have dedicated AI keys on new PC keyboards. With billions in capital to spend, could Apple become the leading AI company? Ask Siri, maybe. BY KIT EATON @KITEATON

USING THE WRONG AI CAN CREATE PROBLEMS. IT'S IMPORTANT TO STUDY DIFFERENT MODELS AND MAKE THE RIGHT CHOICE FOR FOR YOUR BUSINESS

Incorporating artificial intelligence into daily operations can set a business apart. However, recent developments suggest both IBM's Watson and Amazon's Alexa have encountered challenges, underscoring the importance of a cautious approach to integrating AI into your business strategies.

Here's a closer look at the future of conversational AI in business analytics and why you must carefully evaluate its integration into these processes.

The revolution of conversational AI in business analytics

The underlying natural language processing in conversational AI allows businesses to interact with data and customers in a more intuitive and human-like manner. The upsides are obvious: from enhancing customer service with AI-driven chatbots to enabling more accessible data analytics through conversational interfaces.

As far back as 2016, IBM's Watson promised incredible leaps ahead in analyzing complex data sets, notably through initiatives like Watson Oncology at the Memorial Sloan Kettering Cancer Center. But although there was much promise and millions of dollars poured into its further development, it came up short. Watson was discontinued in several Genomic projects, as shared in a New York Times report in 2021.

As a recent CNBC article reports, IBM decided to bring Watson back, marketing it as a platform for training other machine learning models. With any evolving technology, there will be highs and lows, and this is a great example of the long arc of innovation when it comes to era-defining technologies like AI.

Similarly, Amazon's Alexa has been a leader in incorporating voice-activated technology into daily business and consumer environments through its incubator programs since 2020, offering a user-friendly interface that enhances operational efficiency and customer experience. More recently, Amazon announced it's combining Alexa with LLM technology to create a more compelling chatbot experience.

IBM's Watson and Amazon's Alexa exemplify the evolving impact of conversational AI in business and how it changes over time.

A reality check on conversational AI

Despite their advanced capabilities, potential benefits, and recent developments, both Watson and Alexa have faced their share of challenges. A 2024 Business Insider report reveals that Amazon has been thinking about introducing a subscription model for Alexa, an idea that signals possible difficulties in monetizing the technology source. Such developments raise questions about the long-term viability and cost implications of incorporating conversational AI systems into business operations. For entrepreneurs and startups operating on tight budgets, the prospect of additional subscriptions or unforeseen expenses can be a significant concern.

Businesses attracted by the promise of conversational AI and decision-making tools must navigate the gap between expectations and reality.

The lessons here are twofold: First, the importance of tempering enthusiasm for new technologies with a critical assessment of their current capabilities and limitations, and second, the need for ongoing evaluation of these tools as they evolve.

Navigating the pitfalls by overcoming AI challenges

The allure of conversational AI technologies like Watson and Alexa is undeniable. Many new NLPs are coming into the market all the time. At my company, Aigo, where we provide cognitive AI solutions, I preach the importance of careful implementation with thorough use cases that provide a foundation that can be leveraged for faster internal development and activation.

It's essential to approach integration with caution. You should keep several key factors in mind:

1. Cost Versus Benefit Analysis: Understand the full scope of costs involved, including any potential subscriptions or additional fees. Evaluate whether the benefits of integrating AI technologies outweigh these costs, especially in the early stages of your business.
2. Realistic Expectations: Set realistic expectations for what these technologies can achieve. While AI can offer valuable insights and efficiencies, it is not a silver bullet for all business challenges.
3. Ethical and Privacy Concerns: Conversational AI involves the collection and processing of vast amounts of data, including potentially sensitive information. Businesses must ensure they adhere to data protection regulations and ethical standards, safeguarding customer privacy and trust.
4. Technical Support and Expertise: The integration of AI technologies requires a certain level of technical know-how. Consider the availability of technical support and the need for in-house expertise to manage and optimize the use of these tools effectively.
5. Scalability and Flexibility: As your business grows, your needs will change. Assess whether the AI solutions you're considering can scale with your business and if they offer the flexibility to adapt to evolving requirements.

The opportunities and challenges are multiplying

The journey of integrating conversational AI into business operations is fraught with both opportunities and challenges. By conducting thorough due diligence and maintaining a critical eye, businesses can harness the power of AI to drive innovation and growth while avoiding the pitfalls that have trapped others. In doing so, they can move closer to realizing the full potential of conversational AI in shaping the future of business analytics and customer engagement.

EXPERT OPINION BY SRINI PAGIDYALA, CO-FOUNDER, AIGO.AI @SRINI_PA

THE OPENAI CEO's REMARKS MIGHT RAISE A FEW EYEBROWS, BUT NOT IN A WAY YOU MIGHT EXPECT

The most popular iteration of OpenAI's ChatGPT -- the generative AI chatbot that's taken the world by storm and amassed 100 million daily users -- "kinda sucks," according to Sam Altman, the company's CEO. 

Altman struck the critical tone on an episode of The Lex Fridman Podcast, released Monday. The conversation covered a wide area related to generative AI and the torrent of hype and gold rush that's followed since the commercial release of ChatGPT in November, 2022. 

Fridman called GPT-4 "amazing" and "historically impressive," and described the evolution of different iterations of the tech as fostering "a historic, pivotal moment" in the world. 

In response, Altman cut a pensive figure, stroking his chin, and said "I think it kinda sucks." He explained his thinking with a comparison to how some people might look back on past versions of the iPhone and think that they're useless compared to current models. "I think it is an amazing thing," Altman said, giving his company some credit for its first commercial product, which it released for free. GPT-4, by contrast, is available starting at $20 a month. 

Founders might empathize with Altman's chilly review of his company's technology. Every viable product has to start somewhere, and self-criticism can be harnessed in positive ways. 

The context around Altman's comments is crucial, particularly as generative AI technology evolves at a rapid clip, Altman emphasized. 

"At the time of GPT-3, people were like 'this is amazing, this is [a] marvel of technology,'... and it was. But now we have GPT-4, and you look at GPT-3 and you're like 'that's unimaginably horrible,' " Altman said. 

Altman addressed the next version of the ubiquitous chatbot, presumably called GPT-5, saying "I expect the delta between 5 and 4 will be the same as between 4 and 3. It's our job to live in the future and remember that our tools are going to kind of suck looking back at them." 

OpenAI's next big product doesn't have a release date, and the rumor-mill has been chugging along, with people on Reddit particularly buzzy with speculation about what the company will unleash and when. Asked by Fridman whether GPT-5 will be released this year, Altman said "I don't know. That's an honest answer." 

Though he did say, "We will release an amazing new model this year." It's unclear what the company will call it if not GPT-5

How much time will need to elapse after the release of this forthcoming model for Altman to believe it "sucks" is a question nobody can answer. 

AN ANALYSIS OF 5 MILLION JOB POSTINGS SHOWED THESE ARE THE 3 JOBS BEING REPLACED BY AI THE FASTEST

I've resisted writing about how AI will affect the job market because, frankly, I had no idea what to say. Since the explosion of generative AI tools on the scene, I've read reputable-sounding research saying everything from, "Don't worry, AI is leveling the playing field," to "Run for the hills, the robot apocalypse is nigh!" (OK, I might be paraphrasing slightly with that last one.)

These studies are not only often contradictory but also generally based on observations of small sets of carefully chosen workers in specific situations. They may tell you AI helps call center workers be more productive, or is causing one company to hire less customer service reps. But it seemed dangerous to draw wider conclusions on such an important subject from limited data.

But I just found one analysis that seems worth sharing, both because it looks at a very broad set of real-world jobs and because these particular jobs are the ones many self-employed Inc.com readers are likely to care about most -- freelance gigs. The news isn't good for three types of professionals in particular.

The jobs that are safe from AI (for now)

This analysis, from labor market trend publication Bloomberry, looks at publicly available data on more than 5 million jobs listed on freelancing site Upwork from a month before ChatGPT was released in November 2022 to just last month.

Researcher Henley Wing Chiu explains why they took this approach: "If there's going to be any impact to certain jobs, we'll probably see it first in the freelance market because large companies will be much slower in adopting AI tools."

Freelancers are essentially the canary in the scrappy, independently operated coal mine. What tune are they singing? That depends on what industry they're in. Wing Chiu observes that most freelance niches are doing just fine despite the ongoing generative AI revolution. Of 12 subcategories he looked at, the vast majority had actually seen the number of jobs listed increase since late 2022.

"Video editing/production jobs are up 39 percent, graphic design jobs are up 8 percent, and Web design jobs are up 10 percent. Software development jobs are also up, with backend development jobs up 6 percent and frontend/Web development jobs up 4 percent," he reports.

Unsurprisingly, postings looking for people with AI skills were also way up. "Jobs like generating AI content, developing AI agents, integrating OpenAI/ChatGPT APIs, and developing AI apps are becoming the rage," Wing Chiu says.

And those that need to worry

But there were three big exceptions. With apologies to my fellow word nerds, those were writing, translation, and customer service jobs. "The number of writing jobs declined 33 percent, translation jobs declined 19 percent, and customer service jobs declined 16 percent," the Bloomberry analysis found.

This is hardly the biggest shock, as some of the earliest and most developed use cases for AI are basic copywriting tasks and customer service chatbots. Swedish buy-now-pay-later startup Klarna just announced that its customer service chatbot is doing the work of 700 customer service reps, for instance, and the media has been full of stories of writers who have lost their jobs to AI replacements.

This data confirms what writers have already feared, but does it mean that video editors and graphic designers should rest easy? Wing Chiu isn't so sure. The uptick in these sorts of jobs, he warns, may be temporary, as companies figure out how to best use fast-improving video and image generation tools.

"I think there's several ways to interpret this data. One is that these generative AI tools are already good enough to replace many writing tasks, whether it's writing an article or a social-media post. But they're not polished enough for other jobs, like video and image generation," he writes.

It might also be that companies are still figuring out how best to use these tools. There was a lag of six months or so between the release of ChatGPT and the biggest decline in writing jobs. Companies might just need more time to figure the more complex case of video and image manipulation. If that's so, declines in many other fields just haven't quite arrived yet.

Whichever of these possible scenarios turns out to be correct, freelancers and entrepreneurs in fields likely to be touched by AI probably shouldn't be sitting around twiddling their thumbs and hoping it all works out.

Exactly how fast AI will come for rote and routine jobs in various sectors remains an open question no single research project can definitively answer. But whatever the exact contours of AI disruption, creativity, social savvy, agility, and dealing with ambiguity are likely to remain exclusively human domains for a long time yet. If you're worried about AI's impact on your industry, the time to make these skills central to what you offer is now.

EXPERT OPINION BY JESSICA STILLMAN, CONTRIBUTOR, INC.COM @ENTRYLEVELREBEL

AN INTUIT STUDY FINDS WOMEN ENTREPRENEURS AROUND THE WORLD WANT TO USE AI MORE FOR THEIR BUSINESSES

Female entrepreneurs in the developing world are increasingly looking to technology to help them run their businesses. More than half of these business owners intend to spend more on tech in 2024 compared to 2023, leading to a 37 percent increase in projected tech-related spending this year.

That's according to a report out today from software company Intuit and the Cherie Blair Foundation for Women, founded by former British first lady Cherie Blair. The report also found that 44 percent of respondents are already using artificial intelligence for their companies, primarily for content generation and editing, and that two-thirds felt that training was the main barrier to more adoption of generative AI. That creates an opening for major software vendors and smaller companies to both empower and sell their products to female entrepreneurs by providing targeted training.

The report, based on a survey of more than 1,100 female business owners in 81 low- and middle-income countries, estimates the total market for providing digital tools for such women is about $30 billion.

The vast majority of respondents -- nearly 93 percent -- use the internet on a daily basis to run their businesses. They say that high prices for services and equipment, online harassment, and unreliable networks are among their biggest concerns.

The report urges tech and digital service companies to develop "a more nuanced understanding of local markets" as well as the specific needs of women entrepreneurs. Paying attention to local needs and conditions could help companies introduce their products to new markets where high volume can make up for low margins, the report notes.

Ninety-two percent of the women surveyed access the internet through smartphones. WhatsApp was the most commonly used app, followed by popular social-media networks. The report identifies an opportunity for growth in the digital payments and e-commerce space since less than a third of respondents currently use mobile money and digital payments services.

HOW TO USE THE POWER OF CONVERSATIONAL AI IN HR

Artificial intelligence can help you recruit, hire, and engage with your employees better than ever before. However, expert insights are critical in helping businesses navigate and effectively implement AI solutions. Recent research from McKinsey indicates that AI-driven systems can handle up to 70 percent of routine HR inquiries. The goal is not just automation for small businesses but also aligning HR operations with strategic business objectives, leading to enhanced productivity and workforce satisfaction.

Here's how to bring AI on board without breaking the bank or angering your employees.

Conversational AI in recruitment and onboarding

Revolutionizing recruitment and onboarding includes providing a seamless and efficient experience for both employers and candidates. Through AI-driven chatbots and virtual assistants, the recruitment process becomes more interactive, with AI efficiently handling initial candidate queries, scheduling interviews, and even conducting preliminary screenings.

During the onboarding process, AI helps employees through the training process by providing easy access to compliance guidelines, updates, and answers to other routine inquiries, all of which frees up HR reps. For small businesses, this means better resource allocation to critical areas, enhancing overall productivity without compromising quality.

A recent University of Southern California article provides insights on how AI allows HR reps to do their job better, connecting with prospects sooner and increasing satisfaction for everyone involved. Turning manual tasks over to AI increases the humanity in human resource departments because it means HR reps don't exhaust themselves on repetitive, attention-draining tasks.

Conversational AI-driven employee engagement and feedback

Conversational AI tools create a platform for continuous dialogue and feedback, proven to increase engagement levels by up to 30 percent. AI-facilitated surveys and feedback mechanisms allow employees to voice their thoughts and concerns in real-time, fostering a more inclusive and responsive workplace environment. The technology's ability to analyze employee sentiments provides valuable insights, enabling timely and effective responses to workplace issues.

Of course, there might be concerns about employees not feeling comfortable talking to chatbots. Removing humans from the process is not the goal. Implementing effective AI-driven engagement means at any time staff can ask chatbots to connect with an HR rep. However conversational AI is becoming more sophisticated and capable. A 2018 article from CNBC talks about how during one interview process, 73 percent of candidates didn't even know they were talking to an AI chatbot -- and AI comprehension and capacity have improved dramatically since then.

Conversational AI in training and development

Regarding training and development, conversational AI is making significant strides, particularly in small businesses. AI tools create dynamic learning models that allow trainees to explore responsive platforms that engage with their specific learning preferences. For example, AI can create real-time simulations of real-world situations which give employees a chance to try and fail without consequences.

Managing HR compliance with conversational AI

Managing HR compliance with conversational AI is becoming increasingly crucial in the modern business environment. By integrating AI into HR systems, companies can ensure adherence to complex labor laws and regulations more effectively.

For example, AI can automate the tracking of employee work hours, leave, and benefits, thus reducing the risk of noncompliance with labor standards and wage laws. This tech-driven approach not only streamlines compliance management but also enhances overall operational efficiency in HR departments.

A study by PwC found that 44 percent of companies using AI in HR reports improved compliance. By leveraging AI for data management, small businesses can navigate the complexities of HR compliance with greater confidence and efficiency, ensuring that they remain focused on growth and operational excellence.

Streamlining HR efficiency and compliance through AI

The process of implementing and improving HR operations in this new AI era requires a balanced approach. Give your HR reps more time to handle complicated tasks while providing employees more opportunities to get information and responses quickly. Turn your hiring process into an incredible funnel for sussing out better candidates more often and providing them with easier methods to onboard into your company culture. Don't replace the human touch, improve it, because, at the end of the day, AI is trained on our behavior.

EXPERT OPINION BY SRINI PAGIDYALA, CO-FOUNDER, AIGO.AI @SRINI_PA

NVIDIA'S CEO THINKS AI WILL BE SMARTER THAN HUMANS IN 5 YEARS. WHY WE SHOULD LISTEN UP

Nvidia CEO Jensen Huang recently reiterated his view that society is five years out from having artificial general intelligence, or AGI, technologies that are capable of many of the same sorts of intellectual tasks as humans. These prospective technologies, he noted at an economic forum held at Standford University, are expected to be capable of many of the same sorts of intellectual tasks as humans.

His comments follow the statements he made during a New York Times DealBook Summit in November where he claimed AGI advancements are just five years away. Huang said that if you were to pose some of the same intelligence tests as are given to humans, in five years' time an AI will likely "do well" on "every single test you can possibly imagine."

Right now AI systems can pass some standard human tests -- witness recent headline-grabbing efforts like OpenAI's ChatGPT GPT-4 passing bar exams -- but struggle with more specialized topics. So while Huang is holding back from saying we'll soon see the emergence of a fully intelligent machine system -- something like the operating system from the sci-fi movie Her, capable of human-like interactions and problem-solving -- he can see that the current crop of slightly clunky, hallucination-influenced, unreliable AIs will very quickly develop into much cleverer systems.

Huang also underlined that the world will need more chip fabrication factories to enable AI to advance. This chimes perfectly with news that his company's stock price at closing on Friday marked the first time Nvidia closed with a value above $2 trillion. It also supports, in a way, OpenAI CEO Sam Altman's calls for trillion dollar-scale investment into new chips designed to process AI algorithms. Huang's overall point about AIs becoming smarter is also supported by recent work by scientists who found that very large chatbot AI systems are exhibiting tiny glimmers of understanding.

Huang did temper his bold prediction about AI's growth by noting that scientists are still working hard to fully understand how human brains work, so defining what a full artificial intelligence is may well be something of a moveable feast. That's supported by one of the co-founders of Google's DeepMind AI division, who recently argued that standard tests for how smart AIs are don't work well. According to Mustafa Suleyman, a better test would be if an AI could be a CEO of its own company; he pegged 2030 as the date by which he was certain AIs would be smart enough for this task.

But what does all this mean for everyone who's busy incorporating AI into their daily home, school, and work life today -- pressing Microsoft's new AI keyboard key and quizzing AIs for answers that previously they'd have posed to search engines? Not much, not right now. The debate on whether or not AI is directly threatening many people's jobs is ongoing, and expert opinions on the matter differ -- even if AI may have played a role in some of the recent high-profile tech industry layoffs.

Cleverer AIs will almost certainly emerge over time, as Huang says, but this is a revolution happening over years, not months. Industries that are likely to benefit from AI will have time to evolve and to choose how they use AI systems alongside workers. For example, when Adobe last week revealed a prototype AI system that can create music, the company was careful to note that the future of music creation probably involves a musician working with AI systems as a force multiplier instead of simply being replaced by the machine.

GENERATIVE AI COULD HELP VIDEO GAME DEVELOPERS COMPLETE MONTHS OF WORK IN MINUTES. CAN IT SAVE YOUR BUSINESS?

The video game industry needs a hero, and artificial intelligence might just save the day.

While 2023 was widely-regarded as one of the best years ever for gaming, with a record-breaking number of critically acclaimed releases, there were warning signs that the good times wouldn't last. Venture capital firms invested just $4.1 billion into gaming companies in 2023, a far cry from the $14.6 billion invested in 2022 and the $16.2 billion invested in 2021, according to a recent report from the research firm Pitchbook. Now dealing with reduced funding, the $184.3 billion video game industry--like many businesses across sectors--is hoping AI can help it bridge the gap between its ambition and its resources. 

The reduced VC activity "likely represents a more realistic level of investment than the peak years of 2020 to 2022, which attracted non-endemic and 'tourist' investors during Web3 and metaverse hype-cycles," according to the Pitchbook report. Large gaming companies used the influx of funds from 2020 to 2022 to scale up their staff in order to take on hugely ambitious games with budgets topping $300 million. In this suddenly more difficult funding environment, those same companies have been undergoing massive layoffs and are scaling their ambitions back down. Just in the past few weeks, Sony announced it would lay off 900 PlayStation employees, Microsoft said it would lay off 1900 Xbox employees, and Electronic Arts said it would lay off around 670 employees, or 5 percent of its workforce. 

"The party is over," according to Ilya Eremeev, co-founder of gaming-focused VC firm The Games Fund. "Now it's time for the hangover." Eremeev says that these inflated budgets can "make your margins so thin that even games with great reviews and sales can still be unprofitable, because the development cost is so high." 

So, how are these developers supposed to execute on their still-ambitious visions with diminished resources? The answer, at least according to a few major players in the gaming space, may very well be generative AI. In November, Japanese gaming titan and Final Fantasy creator Square Enix announced an investment in Atlas AI, a startup providing game developers with genAI-powered tools for the creation of 3D assets and models, essentially the "stuff" that makes up a digital world, like buildings, landscapes, and props. Atlas scans reference images like concept art and mood boards to understand the aesthetic a designer is attempting to achieve, and then renders a "catalog" of 3D assets that can be further customized by artists. 

Atlas' founder, Ben James, a former architect, started the company with an ambition to create a tool that could scan architectural plans and blueprints, and instantly render a high-quality 3D version of the project. But in speaking to representatives from various industries that were interested in the tool, it became clear to James that "the scale and speed at which game developers build necessitated this type of technology." 

The amount of computation needed to create huge-scale game worlds with hyper-realistic graphics has increased exponentially over the past decade, according to James. In addition to being expensive and requiring huge amounts of manpower, designing these worlds is a lengthy process that often leaves little time for revisions. "If you've spent six months developing a particular style for your game" says James, "you're going to be pretty hesitant to leave that style. With AI, you can change those style references and generate a whole new world in minutes. It's going to allow developers to be way more flexible in the early stages of the design process." 

"In recent years, the rising cost of game development has been challenging for the entire game industry, and gen AI is expected to help streamline the process in new and exciting ways," Square Enix general manager Hidekai Uehara said in a statement. "We are excited about Atlas' unique technology and look forward to seeing how it might unlock efficiencies in our business."

Kylan Gibbs, CEO and co-founder of Inworld, a startup developing generative AI-powered tools for the creation of non-playable characters and story elements in games, shares Uehara's belief that AI can be used to streamline existing development flows. In November, Inworld announced a sweeping partnership with Xbox to develop a generative AI-powered tool that would speed up the process of narrative development in Xbox games. According to Gibbs, most game writers at major studios have to go through dozens of steps before they get a sense of if an idea they had months ago is actually any fun to play. With the generative AI tools being built by Inworld, Gibbs says writers could create a playable demo for internal use "in minutes instead of months." 

It's not just big gaming companies that are getting in on the AI action, as smaller studios are also making clever use of more consumer-friendly generative AI to drive efficiency. Rob Lester, chief creative officer at Michigan-based independent game studio Zollpa, has used ChatGPT to speed up his team's quality assurance and playtesting process, essentially the process of poking and prodding the game to find bugs and address gameplay issues. 

Unlike large studios, which often employ hundreds of contractors to perform QA services for their games, Zollpa's team of eight conducts QA and playtesting entirely in-house. For Zollpa's latest game, an online arena shooter called RoboSquad Revolution, Lester had the idea to record the team's QA sessions, upload a transcription of the audio to ChatGPT, and ask the chatbot to analyze the document, noting any instances in which bugs or issues were mentioned. Those notes were converted into action items, which were automatically assigned to team members based on their expertise. "It streamlines the process of gathering the information we need to act on tremendously," says Lester. "Plus, it's pretty hard to play a video game and take notes at the same time, basically impossible."

Gibbs says we're still a few years away from the release of any major games built to take full advantage of genAI, but outside of gaming, many businesses are much further along when it comes to harnessing AI in meaningful ways. Last week, Klarna announced that its new OpenAI-powered customer service chatbot was doing the equivalent work of 700 employees. In February, Adobe released an AI assistant that can read long documents and answer questions about their content. And a recent survey of companies that rely heavily on AI found that some have seen so many productivity gains that they're considering instituting a four-day work week.