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Survey: 37% of Professionals Save 5-10 hours a Week Using Generative AI Tools

Contentful has released the findings from its inaugural Generative AI Professional Usage and Perception Survey, shedding light on the perceptions, attitudes and usage of generative AI among professionals globally.

Contentful surveyed 820 people across multiple industries, company sizes and countries in various technical and non-technical roles to understand the opportunities and challenges presented by genAI in the workplace. More than three-quarters of respondents have company-paid access to genAI tools at work.

READ: Unveiling the Power and Pitfalls of Generative AI in The Modern Workplace

Nearly a quarter of all respondents find these tools so valuable in a work context that they seem happy to use their own money to access them, either entirely or on top of what their employers fund. Eighteen percent of respondents said they do not expense the genAI tools they buy.

Of all daily genAI users overall, 20% use the tech for professional purposes and 15% for personal use. 38% of respondents say they save from one to almost five hours a week using genAI tools; 37% save between five and 10 hours per week; and 11% save more than 10 hours per week.

For the 11% of respondents who were not using genAI either professionally or personally, most cited the lack of opportunity and access to these tools. Several respondents indicated they were waiting for their companies to develop guidelines or policies on how to use genAI.

More than two-thirds of organizations are considering plans either to apply an existing Large Language Model (LLM) to their own proprietary content or to train their own LLM. Only 31% of survey respondents said they were unaware of any such plans in their organizations. Some (18%) already have plans and a small but forward-thinking 6% have projects underway. Of those organizations that already have or are considering plans for tailored LLMs, 49% are utilizing an existing LLM, and 42% are training their own.

Among the notable findings:

There is a significant gap in excitement for AI between individuals who consider themselves highly knowledgeable about genAI (in particular, those who rated themselves a “5” on a one-to-five scale) and everyone else.

Professionals with high genAI knowledge levels are more actively engaged in using genAI tools, already identifying its productive impact.

The majority of respondents expressed a desire for more guidance on responsible genAI usage, indicating a need for company training and support. Although 36% say they have been given a sufficient amount of guidance from their organization on how to use genAI responsibly, 51% of respondents would like more.

AI vs. Traditional: Which is the Best Approach in Recruitment

Recruiting challenges change constantly, which means you need creativity to stay ahead of the curve and ensure efficient hiring. However, traditional methods, while tried and tested, can struggle to keep pace with the dynamic hiring needs of today’s world. Enter AI recruiting.

From sourcing to candidate assessment, this promising method brings various tools and technologies that help streamline recruitment processes. It can sift through vast volumes of data in real-time, expediting top talent searches and fine-tuning selections based on your parameters.

As such, it isn’t surprising that 45% of companies utilized AI recruitment tools in 2023.

READ: How to Welcome AI in Your Recruiting Process

As businesses shift to AI, the debate between modern and traditional methods intensifies. Each approach boasts its strengths, but they share the same goal: securing the best talent swiftly and effectively.

AI vs. traditional recruitment

The battle between these two methods revolves around efficacy, personal touch and adaptability. AI, with its data-driven precision, battles against the human-centric approach of traditional methods. Here are the strengths and weaknesses, and how they fare in critical recruitment domains.

Speed and efficiency

AI recruiting tools can swiftly scan through resumes, identify patterns and shortlist candidates in a fraction of the time it takes traditional methods. Automated processes expedite initial screenings, accelerating the overall hiring timeline significantly.

Conversely, traditional methods rely on human judgment, often prolonging the process due to manual candidate evaluation and decision-making.

Candidate experience

Traditional methods tend to excel in providing a more personalized candidate experience. Human interactions, through customized communication and tailored processes, contribute to a more engaging and empathetic candidate journey, which is essential for businesses trying to appeal to top talent.

However, AI’s advancements in natural language processing (NLP) and chatbots attempt to bridge this gap, offering instantaneous responses and personalized interactions at scale. Though these AI tools are not quite at the level of consistently passing as humans, developers are constantly improving their function, which may only be a matter of time.

READ: Unlocking the Power of Conversational AI — 6 Game-Changing Applications for Your Business

Bias mitigation

Hypothetically, AI promises to minimize bias in recruitment decisions by basing assessments on data rather than subjective human judgment. However, biases can seep into AI algorithms through training data or flawed equations, leading to unintended discriminatory outcomes. After all, humans tend to influence their creations, often without intent.

Traditional methods, though prone to inherent biases, often have human intervention that can mitigate them to an extent.

Adaptability and flexibility

AI evolves rapidly, constantly learning and adapting based on data patterns and user interactions. This adaptability continuously refines and optimizes processes. Contrastingly, traditional methods may need help to swiftly adapt to changing trends, technology or sudden shifts in the job market.

AI can be particularly helpful when onboarding remote hires since AI-analyzed data can help depict special skills you otherwise wouldn’t have because of the lack of face-to-face interaction — integral when observing an applicant’s soft skills and personal qualities.

READ: AI in the Workplace — A Roadmap For HR Professionals

Cost considerations

Investing in new technologies and tools will almost certainly come with a steep initial price tag. For smaller businesses, it can even be prohibitively expensive. However, in the long run, efficiency gains and reduced time-to-hire can outweigh the initial costs.

Conversely, traditional methods may be more cost-effective upfront, but hidden costs associated with prolonged vacancies, higher turnover rates and increased labor requirements might overshadow these apparent savings.

The Hybrid Model

In reality, the ideal approach is most likely somewhere between these two approaches — a symbiosis that capitalizes on the strengths of both AI and traditional recruitment. Hybrid models are most likely to become greater than the sum of their parts.

AI’s speed and precision near-instantly parses applications based on your minimum requirements and sort those that pass for human intervention.

Your hiring professionals can then add the human touch to make candidates more engaged and your company more relatable to prospects. A person can also make the final decision of hiring based on AI data and the subjective qualities that machines can sometimes struggle to detect.

This last step is for candidates who may appear perfect on paper but may have some less concrete qualities that your company finds undesirable.

Finding the middle ground

Adapting AI in recruitment may seem like a long shot, but it isn’t without basis. Because of the continuous innovations in AI technology, businesses are seeing how they can use it in a plethora of business processes, including recruitment. With proper application, a hybrid model can result in an evolutionary leap in recruitment strategies, benefiting candidates and recruiters alike.

Instead of viewing AI as a replacement for traditional hiring practices, companies should see AI for what it is — a revolutionary tool that offers unprecedented efficiency that thrives in collaboration with human judgment and empathy.

 

Ken Crowell HeadshotKen Crowell is the Founder and CEO of EmployTest. EmployTest has helped more than 7000 corporate and government customers of all sizes in every US state and Canadian province, as well as more than 17 countries across six continents. EmployTest administers more than 60,000 tests to job applicants every year.

How to Welcome AI in Your Recruiting Process

We’ve all experienced the endless circles of frustration and stress that have become the norm as we try to resolve day-to-day issues with the help of a bot. AI has arrived, and it’s everywhere, including in recruitment. However, AI is a tool, not the toolbox. It cannot replace humanity.

READ: AI in the Workplace — A Roadmap For HR Professionals

AI streamlines the hiring process for employers and candidates alike. Among other benefits, it helps candidates optimize their resumes and other documentation and saves them from hours of repetitively filling out applications — which often end up in black holes with no hope of a response. 

By automating tedious manual tasks and much of the pre-selection process, AI boosts recruiters’ productivity and efficiency, decreases time to hire and reduces costs. When technology and humanity work together, the savings in time and money free recruiters to personally respond to candidates at key points. 

Think of AI as additive. Embrace it while preserving the critical human element that fosters connection and makes your company unique. Humans prefer working with humans and we can feel the difference when there’s a person in charge.

You cannot ignore AI

AI exploded onto the landscape in 2022. In this short time, employers in every industry and of every size, from multinationals to small businesses, have embraced it. SHRM reports that 79 percent of employers are currently using AI or another form of automation for recruiting and hiring. Those that haven’t yet adopted AI are planning to soon. The Boston Consulting Group (BCG) aptly calls the current AI revolution “a new order for business and society.” It’s that important.

Here are some of the ways recruiters are currently using AI: 

  • Screening and assessing candidates more precisely and efficiently and identifying those with the right skills and qualifications.
  • Performing boring or repetitious tasks such as interview scheduling and resume screening.
  • Creating clearer job descriptions that more accurately represent the requirements of the job and help attract the right candidates.
  • Using chatbots to search for information and engage with candidates.
  • Asking candidates better questions to make smarter hiring decisions.
  • Reducing the time to hire.
  • Increasing inclusion and diversity in hiring by removing human subjectivity and bias.
  • Customizing or improving compensation benchmarking.
  • Closing gaps among documents, writing better manuals, and standardizing processes.
  • Increasing fairness in hiring and improving candidate and onboarding experiences.
  • Freeing recruiters to provide a more personalized candidate experience with more interaction and engagement. 

READ: Chat GPT isn’t Always the Answer — 4 Reasons for Human-Generated Copy is Still Essential

In addition to enhancing recruiting efforts, employers find AI an effective retention tool. AI can recommend learning and training opportunities and suggest career paths for current employees, aid in performance management, and identify employees who are no longer engaged or are at risk of leaving.

Making AI human

Although people are generally more optimistic than concerned about the use of AI, there are questions in some minds, especially about the prospect of losing jobs to machines. It’s true that switchboard operators or encyclopedia sales reps are a thing of the past. However, we still flock to phone stores, and humans are essential in writing and editing Wikipedia. It is tasks, not people, that become obsolete.

Here are ways that AI and humans can augment each other:

  1. AI performs tasks that people don’t like to do, those that are unsafe or risky, or tedious and repetitive; humans monitor and validate AI’s performance.
  2. AI generates the facts and serves as the first step in analysis; humans generate new questions and solutions based on the facts.
  3. Humans come up with ideas; AI refines and challenges their creative thinking to make ideas a reality.
  4. AI collects data; humans turn it into stories that deepen understanding and connect to your company’s purpose.

The ideal mix of machine and humanity is more of a management challenge than a technology or administrative issue. People at all levels must be upskilled or trained to use AI effectively and responsibly. Everyone in the organization should be educated on the benefits and pitfalls of using AI and understand the expectations around its use in your organization.

Where and when is AI appropriate to use or not? When is human judgment required or desired? When should decisions be based on facts and when are compassion, empathy, and nuance important? Companies that effectively integrate technology and humanity are creating a new definition for business success.

 

Kathleen Quinn Votaw2Kathleen and her firm have achieved many recognitions from many well-known organizations, including ColoradoBiz Magazine, Vistage Worldwide, and the coveted Inc. 5000 for two consecutive years. Kathleen is a regularly published columnist and popular speaker on topics related to HR strategies and workplace culture. Reach Kathleen at [email protected] or (303) 838-3334.

Is AI Revolutionizing the Insurance Market? In Short, Yes.

The insurance industry, historically characterized by manual processes and conservative risk assessment, has seen a remarkable transformation in recent years with the infusion of artificial intelligence (AI). Artificial intelligence has revolutionized the insurance market by streamlining operations, improving customer experiences, and enhancing risk management. In this article, we will explore the significant impact of AI on the insurance sector, its key applications, and the prospects of this dynamic landscape.

READ: AI in Insurance — How New Technologies are Changing the Game

The evolution of artificial intelligence in the insurance industry

The integration of AI into the insurance market is emblematic of the broader digital transformation across industries. Insurers have recognized the potential of artificial intelligence to optimize their processes, reduce costs, and enhance decision-making. This evolution can be attributed to the following factors:

  1. Big data: The advent of big data has enabled insurers to access and analyze vast amounts of information related to customer behavior, demographics, and risk factors. AI algorithms can process this data to identify patterns, trends, and correlations that were previously difficult to discern.
  2. Advanced analytics: AI technologies, including machine learning and deep learning, have empowered insurers to develop predictive models that assess risk more accurately. These models consider a multitude of factors, improving the precision of underwriting and pricing.
  3. Customer-Centricity: AI-driven personalization has allowed insurers to create tailored policies and services that cater to individual customer needs. Chatbots and virtual assistants are used for claims processing, policy management, and customer inquiries, resulting in a more responsive and efficient customer service experience.

READ: 6 Game-Changing Conversational AI Applications for Your Business

Applications of AI in Insurance

AI is applied across various facets of the insurance industry, and its impact is profound. Here are some key applications:

  1. Risk Assessment and Underwriting: AI algorithms evaluate a vast range of data sources, including historical claims data, social media, and IoT devices, to assess individual risk profiles. This enables insurers to make more accurate underwriting decisions and calculate premiums that reflect the specific risk of each policyholder.
  2. Claims Processing: AI-driven automation simplifies the claims process. Chatbots and virtual assistants can gather initial information and guide policyholders through the claims process, speeding up claim settlements and improving customer satisfaction.
  3. Fraud Detection: AI is a powerful tool for identifying fraudulent claims. Machine learning models can detect unusual patterns and flag suspicious activities, helping insurers combat fraud more effectively and save substantial sums of money.
  4. Customer Service: Virtual assistants and chatbots provide customers with 24/7 support, answer queries, and offer policy information. This enhances the overall customer experience and reduces the workload on customer service teams.
  5. Predictive Analytics: AI is instrumental in predicting future insurance trends. It can help insurers identify areas with high potential for losses and adjust underwriting and pricing strategies accordingly.
  6. Customer Insights: Artificial intelligence enables insurers to gain deeper insights into customer behaviour and preferences. This information is valuable for crafting personalized policies, improving customer retention, and enhancing marketing strategies.

READ: AI Revolution — Unveiling the Transformative Power and Unforeseen Consequences

Benefits of AI in insurance

The adoption of AI in the insurance industry brings with it a multitude of benefits:

  1. Enhanced efficiency: Automation and process optimization have resulted in significant time and cost savings. Routine tasks, such as data entry and claims processing, can now be completed more swiftly, allowing employees to focus on more complex, value-added activities.
  2. Improved accuracy: AI-driven risk assessments and underwriting models are more precise and data-driven, minimizing the risk of incorrect policy pricing or coverage. This not only benefits insurers but also ensures that policyholders receive a fair and accurate premium.
  3. Fraud prevention: AI-based fraud detection systems are highly effective at identifying suspicious activities, ultimately saving insurers substantial amounts of money and protecting honest policyholders.
  4. Customer satisfaction: The introduction of chatbots and virtual assistants streamlines communication between insurers and policyholders, providing real-time support and quicker claims processing, ultimately improving the overall customer experience.
  5. Data-driven decision-making: AI enables insurers to make data-driven decisions in real-time, whether it’s in underwriting, claims processing, or risk management. This ensures that decisions are based on the latest information and trends.

READ: AI for Customer Service — 5 Easy Ways to Help Your Customers

Prospects of AI in insurance

The insurance industry is expected to witness further transformation as AI technologies continue to advance. Here are some key areas to watch in the future of AI in insurance:

  1. Enhanced personalization: AI will enable insurers to offer even more personalized policies, tailoring coverage to individual customer needs based on real-time data.
  2. Autonomous underwriting: AI may soon enable fully automated underwriting, where machines assess risks and calculate premiums without human intervention.
  3. Telematics and IoT integration: Insurers will leverage data from connected devices, such as telematics in automobiles and wearable health devices, to fine-tune underwriting and pricing models.
  4. Cyber insurance: As cyber threats continue to evolve, AI will play a pivotal role in assessing and mitigating cyber risks, leading to the growth of cyber insurance.
  5. Regulatory compliance: AI can aid insurers in staying compliant with evolving regulations by automating processes and ensuring transparency in decision-making.

The bottom line

we can say that artificial intelligence is ushering in a new era for the insurance industry, transforming traditional practices into modern, data-driven operations. From underwriting to claims processing and customer service, AI is enhancing efficiency, accuracy, and customer satisfaction.

As technology continues to advance and data sources expand, insurers that embrace AI will be better positioned to remain competitive, make data-driven decisions, and offer tailored services. The future of AI in insurance holds the promise of even greater personalization, autonomy, and an increased ability to adapt to emerging risks, making it an exciting and transformative space to watch.

 

Harish Mukkawar is a highly skilled and experienced digital marketer who has dedicated his career to driving online success for businesses. With a strong passion for data-driven strategies and a deep understanding of consumer behaviour, Harish has become an invaluable asset in the field of digital marketing. Reach him at [email protected].

Smarter House Hunting: How AI Is Changing The Homebuying Process in Mayberry, Colorado

Mayberry, a new community in Colorado Springs, might be inspired by the walkable towns of the past, but it’s taking a cutting-edge approach to selling homes through a partnership with OpenHouse.ai, a fast-growing company pioneering AI real estate solutions. The collaboration offers a new level of convenience and personalization for buyers, centered around affordability and flexibility.

READ: AI-Enabled Real Estate — How Automation is Impacting the Housing Market

AI tools that offer greater efficiency have quickly become commonplace in our daily lives. Now, the real estate industry is embracing the opportunities that AI offers. Mayberry and OpenHouse.ai’s partnership will help buyers find and design the home that suits their budget, needs and lifestyle, while giving builders intelligence into market demand and evolving buyer behavior.

“Our goal is to make it easier for buyers to purchase homes. With OpenHouse.ai, we want to remove barriers for buyers, while being totally transparent about cost. Buyers can complete a questionnaire to identify the best home options based on their needs, interact with floor plans, and get access to the information they need to decide if Mayberry is the right fit for them. After they design and buy their home, they can move in just 120 days later,” said Mayberry Communities President Randy Goodson. “Partnering with OpenHouse.ai makes sense for our market position, buyer profile and our ability to show buyers that we can build top-quality homes quickly through our advanced methods.”

More than ever, buyers are looking for affordable homes that meet their unique and evolving needs. As a result of the pandemic and a move to remote working, for example, Mayberry has seen buyers move away from open-plan layouts to more closed spaces that enable quiet and privacy.

READ: Adapting to the New Norm — Post-Pandemic Work Culture and the Future of Remote Work

“AI is changing the real estate industry. We can provide home builders with meaningful insights in real-time that allow them to better understand what people want from their homes while presenting buyers a range of options tailored to them,” said OpenHouse.ai CEO and Co-Founder Will Zhang. “As the home building industry continues to battle rising costs, labor shortages, and fluctuating demand, AI can also help optimize all aspects of the build lifecycle — including design, procurement and project management — reducing construction cycle times and keeping costs down.”

While AI and automation are transforming how we work, the sales team at Mayberry isn’t concerned about AI taking over their roles. Instead, they see the opportunities it presents. “OpenHouse.ai has been pivotal in enhancing the buyer experience, ensuring it is positive and responsive for our sales associates,” said Mayberry Head Salesman Dean Jaeger. “Each buyer qualified by OpenHouse.ai has been highly communicative, eagerly prepared for the subsequent phase of buying or touring our community.”

By leveraging OpenHouse.ai’s advanced technology, Mayberry is setting new standards for convenience and efficiency, making finding, designing, and buying that new dream home even easier. 

 

About Mayberry, Colorado:

Drawing inspiration from the walkable towns of yesteryears and the rich heritage of early Colorado Springs, Mayberry is set to redefine the “Hometown USA” ideal. With tree-lined boulevards and a pedestrian-centric town center, Mayberry harmoniously blends modern living with nostalgic charm. Here, you can live, work, and play with purpose. Spanning over 110 acres, its trails, parks, playgrounds, and open spaces are crafted to offer leisure just a few steps away from one’s doorstep.

About OpenHouse.ai:

OpenHouse.ai’s Builder Intelligence Platform empowers homebuilders with real-time analytics, facilitating data-driven decisions. The platform has catered to over 2.85 million unique buyers, listing and selling over five thousand homes across major US and Canadian cities, covering 24 Metropolitan Statistical Areas (MSA). Compared to the standard contact conversion rate of 0.5%, OpenHouse.ai-driven personalization boasts a rate of 1.5% to 2.3%. Collaborating with our OSC partners and leveraging an AI-powered quiz can expedite sales by up to 30 days.

Beyond the Basics: 7 Innovative Apps to Help Scale Your Business

Modern businesses must constantly innovate to stay ahead of the curve. The right technological tools can mean the difference between growth and stagnation. As an experienced voice in the business and tech community, I’ve witnessed the transformative power of apps in scaling operations, enriching customer interactions and refining management processes.

From fostering seamless communication to leveraging the prowess of artificial intelligence, the app ecosystem is a treasure trove for businesses aiming to broaden their horizons. In this exploration, we’ll dive into a handpicked selection of innovative apps that promise to elevate your business to new heights. Let’s embark on this digital odyssey together and unlock the potential that these technological marvels hold.

READ: AI for Customer Service — 5 Easy Ways to Help Your Customers

Comprehensive communication tools

In the realm of communication, businesses thrive on clarity and immediacy. Apps like Slack and Microsoft Teams have revolutionized how we connect with our teams and clients. These platforms offer a robust suite of features including instant messaging, file sharing and integration with numerous productivity tools, ensuring that your communication is as seamless as your workflow.

By adopting these comprehensive communication tools, you’re not just fostering a collaborative environment, but also streamlining your processes for efficiency that scales.

READ: 5 Tips for Building a Strong Company Culture in a Hybrid Work Environment

Marketing automation and customer engagement apps

Engaging with customers and automating marketing processes has never been easier, thanks to apps like HubSpot and Mailchimp. These platforms are powerhouses in automating marketing campaigns, managing leads, and analyzing customer interactions. They provide a wealth of data-driven insights that enable personalized experiences, which are crucial in converting leads into loyal customers. In this digital age, a strategic, data-informed approach to customer engagement is not just recommended, it’s essential.

Sign language apps for inclusive customer service

Inclusivity in business is not just a moral imperative; it’s a competitive advantage. Thankfully, there are some excellent courses and free apps to learn sign language on the market that can help your customer service team facilitate communication with the deaf and hard-of-hearing community.

This expansion of your customer base showcases your brand as one that values accessibility and inclusivity. By leveraging these free resources, businesses can break down communication barriers, reflect a commitment to diversity and open up to untapped market segments, all while fostering a positive brand image.

READ: Marketing with Accessible Content — Utilizing User Experience to Build an Effective Campaign

Operational efficiency through management apps

Operational efficiency is the backbone of any scaling business. Project management apps such as Asana and Trello offer a bird’s-eye view of your business’s operations with real-time updates and task management features. They help eliminate bottlenecks in workflows and ensure that your team is focused on what they do best. Embracing these tools can significantly reduce operational overhead and propel productivity to new levels.

Financial management and budgeting apps

Financial clarity is critical in business decision-making. Apps like QuickBooks and FreshBooks have simplified financial management with user-friendly interfaces for tracking expenses, managing invoices and budgeting. They provide comprehensive financial reports that help in forecasting and making informed budgetary decisions. Integrating these financial management apps can offer you peace of mind and a clear financial trajectory for your business, helping your business to stay agile in its financial operations .

Leveraging AI for business growth

Artificial Intelligence is no longer the future; it’s the present.

AI-driven apps like Zendesk and Drift use sophisticated algorithms to enhance customer service, predict market trends and personalize customer interactions. They are capable of processing vast amounts of data to offer insights that human analysis could miss. AI apps can transform your customer service from reactive to proactive, anticipating customer needs before they even arise.

READ: Artificial Intelligence for Social Good — Transforming Global Challenges with Innovative Solutions

Sustainability and green apps

Sustainability is a pressing global concern, and green apps provide a pathway for businesses to contribute positively. Apps like JouleBug and Oroeco help businesses track and reduce their carbon footprint, aligning operations with eco-friendly practices. This not only helps the planet but also resonates with the growing demographic of environmentally conscious consumers, bolstering your brand’s reputation and customer loyalty.

The bottom line

In the digital dance of business growth, these apps are the rhythm to which forward-thinking companies move. They are not mere tools but partners in your journey towards expansion and success. As we’ve seen, whether it’s through enhancing communication, streamlining operations or embracing inclusivity, each app offers a unique contribution to the growth of your business.

We encourage you to not just consider these apps but to integrate them into your business model. In doing so, you prepare your venture for a future where scale and reach are limited only by imagination. Let’s harness these digital solutions and pave the way for a future that’s efficient, inclusive, and sustainable.

 

Stefan Cvetkovic HeadshotStefan Cvetkovic is a seasoned content creator, link-building specialist and team lead, and a young startup leaders who is always on top of all innovations in the world of technology, marketing, and SaaS. Used to wearing many hats, his experience extends to both technical and people roles – from creating growth marketing strategies to project management.

How AI-Powered Content Production Will Transform Digital Creation in 2024

AI is undoubtedly one of the most talked about topics of 2023 and, in particular, utilising AI for digital content production has seen a rise in popularity recently, with online searches for ‘AI generated video’ increasing by 1,257% year-on-year, and ‘AI video creation’ rising by 2,500% in the same time.

It has never been so important for brands to leverage these advancements in technology and use them to support with digital content production. However, it is also crucial for brands to understand that, while AI can support content production and marketing strategies, human thought and insight is still crucial.

READ: AI Content and Human-Generated Copy — A Winning Combination for Social Media Marketing

From ideation to personalization, the team at Bareska has revealed four ways that AI can support your digital content production as you prepare your marketing strategy for 2024.

1. AI enhances the content ideation process

AI can offer hundreds of ideas in just a few seconds, which may then spark further inspiration for your content production team. It can provide a starting point to help avoid a ‘blank page’ mentality where you may be struggling to come up with your very first idea. 

With tools such as ChatGPT, you can input all of the requirements of your campaign and receive AI content ideas and suggestions that will meet your brief. Generative AI can also help to visualize a concept to test whether it could be feasible as digital content.

When using AI for content production as part of the ideation process, you should be aware that there are many pros, cons and risks involved, some of which include:

  • Pros: ChatGPT is a democratized software, which means it’s a free tool. You can receive immediate results and long-form text in seconds. AI can also reduce costs, improve ROI and improve customer experience.
  • Cons: Generative AI is not always accurate, and it’s prone to technical errors and ‘hallucinations.’ Also, if the training data is biased, the output can be flawed.
  • Risks: There are data security risks with ChatGPT, because the program has access to all the data you input into the free version. Research done by Cyberhaven, a data security company, found that 11% of data that employees paste into ChatGPT is confidential and 4% of employees have pasted sensitive data into it at least once.

READ: AI in Journalism — Transforming News Reporting and Storytelling (For Better or For Worse)

2. AI can automate elements of digital content production

To create engaging, high-quality, data-led content that makes an impact, every detail needs to be given attention, which is why it will come as great news that AI can automate certain aspects of your digital content production to make it more efficient, including scriptwriting, editing and voiceovers.

AI can also automate some of the important parts of digital content production to make the content accessible to all users, for example:

  • Automatically producing captions.
  • Translating content.
  • Adding transcripts.

Once you have successfully used AI to produce something, whether that be a caption or a type of edit, it can generally replicate that task accurately over and over again which means you can save time on future content production.

Automating certain elements of your content production also enables time at the end of production for manual quality checking and ensures consistency across all your content, which can strengthen your brand identity and have more of an impact on consumers.

3. AI enables you to create personalized, data-led content

AI has access to immense amounts of data and can be used to gather information before creating content — this may inform the direction of your content, the angle or even the location if you are shooting a video. 

AI can also analyze audience data and gather insights so that you can create content tailored to your audience’s interests and engagement habits. This can have many benefits for your content, including:

  • Increased conversion rates.
  • Brand loyalty.
  • Increased trust between you and your consumers.
  • Better understanding of your target market.

When utilizing AI to analyze data, you should keep in mind that all AI platforms are open source which means you need to be mindful of security, and sensitive data that you input. 

READ: AI Revolution — Unveiling the Transformative Power and Unforeseen Consequences

4. Utilise AI for innovation and stand out from your competitors

Brands are using AI, but not always to its full potential. That being said, one of the biggest ways AI can support your digital content production is by positioning you as an innovator and pioneer in your industry.

You can take a simple, basic idea and use AI to generate original, fun and out-of-the-box concepts. Ultimately, AI can support your digital content to stand out from your competitors through personalization, data and quality assurance. While AI won’t and can’t replace human insight, it can complement and elevate it.

 

Carly Watson headshotCarly Watson is the Managing Partner at Bareska, a content solutions provider that specializes in creating immersive brand and digital experiences. With two decades of experience working in Branded Content, Carly has a passion for innovation and a commitment to pushing the boundaries of creativity to deliver projects that align with client’s brand and communication strategies.

Unveiling the Power and Pitfalls of Generative AI in The Modern Workplace

Artificial Intelligence, commonly known as AI, has been all over the news recently, from goofy uses (George Washington with a mullet) to apocalyptic fears (AI systems with the power to launch a missile attack without human intervention). Forms of AI, like predictive texting, have been around for many years, but generative AI applications are expanding rapidly. 

READ: AI Revolution — Unveiling the Transformative Power and Unforeseen Consequences

Generative AI is capable of generating text, images or other media using models that review patterns to generate similar results. AI has the capability to quickly process large volumes of information and handle many mundane and repetitive tasks. The potential beneficial applications in the workplace are limitless, but so are the concerns. 

One major concern is that generative AI is prone to “hallucinations” where it creates fictitious results that appear to be responsive. We’ve all heard about the attorney who filed a brief written by AI that cited cases that were completely invented by ChatGPT. It’s not always clear how generative AI determines the answer to your question.

There are also concerns about the data sources incorporated into generative AI programs. First, many of these data sources include copyrighted, trademarked or other confidential or proprietary information without attribution or payment to the owners of the information. There are a number of litigation matters pending about this issue.

READ: AI in Journalism — Transforming News Reporting and Storytelling (For Better or For Worse)

Second, it is unclear exactly what information is incorporated into many generative AI models. If the underlying data is unreliable, inaccurate or biased, the generated results will also be flawed. This is a great example of the adage “garbage in garbage out.”

Furthermore, with public generative AI databases, any information submitted as part of inquiries becomes part of the model. This creates significant confidentiality concerns for attorneys and other practitioners who deal with confidential or proprietary information.

An additional concern is how AI might be used to further human actions that are already viewed as problematic and deceptive. AI tools may be especially adept at implementing dark pattern marketing and sales practices or implementing deep fake technologies that will help fraudsters evade even the most sophisticated cybersecurity systems.  

Legislative and regulatory bodies are racing to understand the potential applications and implications of generative AI. Congress has held hearings on AI and is considering a wide range of regulations, as are a number of state legislatures. A bevy of alphabet soup agencies, including the National Institute of Standards and Technology, Federal Trade Commission, Department of Justice, Securities Exchange Commission, Equal Employment Opportunity Commission, Department of Labor, Consumer Financial Protection Bureau, Department of Health and Human Services, and Food and Drug Administration have issued regulatory guidance, proposed regulations or other statements about AI matters.

 

Jackie Benson headshotJackie Benson has two decades of experience counseling entrepreneurs, companies, and investors about corporate transactions and contracts, including organization, mergers and acquisitions, state and federal securities law, private equity, venture capital, financing, restructurings, and other corporate compliance issues and commercial agreements.

AI in the Workplace: A Roadmap For HR Professionals

Artificial intelligence (AI) is an exciting new frontier that is becoming more readily accessible to the public. As governments grapple with the right approach to regulating AI, legal risks are already present, including potential perils for employers arising from concerns around bias and discrimination, as well as copyright infringement, inaccurate data and privacy considerations. Now is the time for all employers to consider implementing explicit policies regulating the use of AI in the workplace.

READ: AI Revolution — Unveiling the Transformative Power and Unforeseen Consequences

Government oversight

There is an emerging patchwork of laws that impact companies’ use of AI. For example, New York City, Illinois and Maryland already have enacted laws regulating employers’ use of AI in the hiring process. The European Union is considering the first comprehensive piece of AI legislation that would regulate various areas, including employers’’ use of AI. Colorado legislators have indicated that they will join a multistate task force to create model AI legislation this fall.

AI-related enforcement activity is also beginning to take place. On Aug. 9, 2023, the EEOC settled its first lawsuit against an employer who allegedly used AI in a discriminatory way (in this case, to reject older job applicants.)

Uses of AI in the workplace

Against this background of growing government regulation, the uses of AI in the workplace are proliferating, including:

  • Generative AI: Generative AI processes extremely large sets of information to produce new content and can do so in a format the AI tool creates (i.e., images, written text, audible output).
  • Recruitment: AI products are evolving to make recruiting more efficient and effective, including by using predictive analytics to forecast which candidates are most likely to be successful in the role.
  • Predicting misconduct: Various tools claim to identify “hot spots” for potential misconduct and allow management and HR to take action before a problem arises.
  • Retaining talent: Companies are also leveraging AI in their efforts to retain top talent by using machine learning to predict if an employee is likely to depart.

Intellectual property (IP) concerns

AI raises various IP-related issues that employers should be aware of, including:

  • If a company uses AI to create work product, who owns it? Companies should not presume they own any resulting rights in work product. On Aug. 18, 2023, the U.S. District Court for the District of Columbia held that authors of works must be human beings, which excludes machine-authored works: “Human authorship is a bedrock requirement of copyright.”
  • Is there potential liability for copyright infringement if the AI tool uses unlicensed work in generating results or the results incorporate unlicensed work? To date, AI companies generally have not sought permission from copyright owners to use their works as part of the large data sets ingested by AI tools; there is an emerging area of litigation in which authors, artists and major rights holders in various fields assert that AI companies infringe upon their copyrights.

Privacy Concerns

Employers must be aware of the inherent risks associated with disclosing data about their workforces to AI tools and consider the following:

What are the risks associated with the disclosure of personal data to AI tools?

By inputting personal data into an AI tool, an employer may lose control of that data and find it made publicly available or disclosed as the result of a data breach. Employee data is often highly sensitive and the repercussions of inadvertent disclosure can be great.

Is the company still able to comply with requests to exercise data rights as required by applicable law if data is inputted into an AI tool?

Depending on where employees reside, they may have rights to access, correct, delete or stop the processing of their personal data. If that personal data has been submitted to an AI tool, deleting the personal data may be problematic.

READ: Secure Your Business in the Digital Age — Essential Data Protection Strategies

Recommendations for employers

It is not a question of whether employers will need to address AI in the workplace; rather, it is an issue of when and how they should address it. Employers would be well-advised to take the following steps in the short term:

  • Become familiar with what AI is generally and what AI the company is already using.
  • Assemble the right stakeholders to discuss appropriate policies governing the use of AI at work.
  • Consider what uses of AI are appropriate for your workplace and what uses are not appropriate.
  • Incorporate compliance with legal issues in designing your policies, including:
    • Ensuring that AI is not used in a way that could adversely impact any group based on protected characteristics.
    • Providing appropriate notice to candidates/employees concerning the company’s use of AI and obtaining consent as may be required under applicable law.
    • Ensuring that the use of AI does not conflict with any statutory or contractual right to privacy held by candidates, employees or consultants.
    • If applicable, develop and implement a similar policy for how your vendors may use AI.
    • Understand what data AI is collecting and how it is assimilating and using data at an organizational level and at a personal level.
    • Assign responsibility for all aspects of the use of AI within your organization so that roles are clearly understood and accountability exists.

AI offers exciting new opportunities, but it also comes with risks and a degree of uncertainty. By ensuring that they understand the uses of AI within the organization, the way it functions and the end results, employers can utilize AI while minimizing legal risk.

 

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Authors: Brownstein Hyatt Farber Schreck shareholders Luke Glisan (left), Christine Samsel (second to left), Airina Rodrigues (second to right), and Darcy Levy (right). Brownstein’s multi-faceted team works together to give employers a well-rounded assessment of risks.

AI in Journalism: Transforming News Reporting and Storytelling (For Better or For Worse)

The proliferation of generative artificial intelligence (AI) across industries — communications, law, medicine, coding, design — can either be perceived as extremely exciting or deeply unsettling, perhaps even both. In a letter published earlier this year, Bill Gates said the technology is “as fundamental as the creation of the microprocessor, the personal computer, the Internet and the mobile phone.” This is especially true for AI in journalism.

Many companies are at the very least curious about how to integrate generative AI into their business practices, with some already using it. According to a recent survey of global executives by VentureBeat, more than half (55%) of organizations are experimenting with generative AI and 18% have actually implemented it into their operations. Notably, the largest use case was for tasks related to natural language processing, such as chat and messaging, followed by content creation.

READ: Artificial Intelligence for Social Good — Transforming Global Challenges with Innovative Solutions

Tools like ChatGPT and DALL-E hold the potential to transform work as we know it, but we’ve only just begun to scratch the surface of their use cases, parameters and risks. Fortunately, newly released editorial standards and emerging case law have started to build a framework for how to responsibly use AI in journalism.

For readers interested in using tools like ChatGPT, this article will explore guidance issued by newsrooms and the law on how to approach generative AI in journalism, as well as tips for editing AI-generated content.

Newsroom guidelines for generative AI

As it currently stands, generative AI cannot be trusted to produce objective, factually-correct reports on its own.

These programs can have “hallucinations” in which the AI confidently responds to a prompt with an answer that is not justified by the facts of its training data. They are also predisposed to historical biases and societal perspectives. However, this hasn’t stopped newsrooms from dabbling in generative AI to help with things like research, analysis, brainstorming and proofreading.

Some news outlets have started issuing AI-focused guidelines to their staff to ensure it is used consistently and responsibly. The general consensus seems to be that AI can assist with routine tasks, but stories must still be written by humans. Below are a few examples of editorial standards from leading publications about AI-generated content.

  • The Associated Press says generative AI cannot be used to create publishable content and images but is encouraging staffers to become familiar with the technology.
  • The Guardian states that generative AI requires human oversight, and should only be used to contribute “to the creation and distribution of original journalism.”
  • For the Financial Times, their journalism “will continue to be reported and written by humans,” but they will give their team the space to experiment responsibly with the technology for tasks like datamining, analyzing text and images and translation.
  • WIRED does not publish stories with text generated by or edited by AI, “except when the fact that it’s AI-generated is the whole point of the story.” They clarify that they may try using the technology to generate suggestions for headlines, text for short social media posts or story ideas. 
  • Insider tells its staff, “ChatGPT is not a journalist … your stories must be completely written by you.” On the other hand, their team is encouraged to experiment with ChatGPT for things like story outlines, proofreading and summarizing old stories. 

READ: 4 Prompts and Tips for ChatGPT — A Comprehensive Guide for Marketers

Legal implications of generative AI

While it may seem like AI conjures up text and images all on its own, these platforms are trained using data lakes and archives of images and text to recognize patterns, set rules and then draw conclusions. This process raises a number of legal questions around infringement, rights of use, intellectual property and ownership of AI-generated content.

The jury is still out on most fair use cases. In Andersen v. Stability AI et al and Getty Images v. Stability AI, both filed earlier this year, the plaintiffs allege that generative AI platforms used their images to train their AI without permission or compensation. The outcome of both these cases will likely significantly impact the generative AI landscape one way or another. 

On the question of authorship, the U.S. Copyright Office currently does not issue copyrights for AI-generated work. Colorado artist Jason M. Allen found himself at the center of this national conversation after it was discovered that his winning piece at the Colorado State Fair’s fine arts competition was created using AI. Since taking home the blue ribbon in 2022, Allen’s copyright request has been denied three times with the federal office finding he is not the “author” of the image. 

It’s important to stay vigilant when using this technology. If generative AI outputs are found to infringe on copyrights, both the AI user and AI company could be held liable under current doctrines, according to a recent report from the Congressional Research Service. 

READ: AI Revolution — Unveiling the Transformative Power and Unforeseen Consequences

Tips for editing AI-generated work 

As demonstrated, generative AI in journalism may take the hassle out of creating a rough draft, but it doesn’t produce a finished product. Interestingly, ChatGPT seems to agree. When I asked the bot, “Does AI writing need an editor?” It responded, “While AI can automate parts of the writing process, it often benefits from human oversight to produce high-quality, engaging and trustworthy content.”

The main goal of editing AI-generated content is the same as editing human-produced content — to improve readability and accuracy. Here are some things to look out for when editing an AI’s work:

  • Avoid plagiarism issues by checking for originality and ensuring your piece doesn’t too closely resemble others.
  • Make adjustments to match the author’s voice or brand’s personality.
  • Always fact-check or risk ending up like the lawyer in Mata v. Avianca, Inc., who submitted AI-generated documents to the court that contained imaginary case citations.
  • Optimize your content for search engines with relevant keywords and proper formatting.
  • Reframe the piece to ensure it resonates with your target audience.
  • Refine awkward sentence structures.
  • Review for legal and ethical considerations.

If you do use AI to generate content, understand that your conversations with generative AIs belong to the AI company and could show up in answers to other users. Therefore, it’s best to avoid sharing confidential information with these platforms. 

Generative AI holds exciting possibilities for improving productivity, sparking creativity and potentially revolutionizing how we work. As the technology currently stands, though, there are still issues surrounding accuracy, rights of use, authorship and journalistic integrity. Inevitably, businesses are going to integrate generative AI in journalism, and those that learn how to responsibly hone its vast capabilities will come out ahead. 

 

Sara Rosenthal HeadshotSara Rosenthal is a freelance writer and communications consultant based in Denver. Learn more at saramrosenthal.com.