Tag: AI Tools

Danielle, you have an impressive background in both academia and professional services. Could you start by sharing your journey and what led you to your current role at Caseware as VP, Head of Analytics and AI?

My journey to my current AI and analytics role at Caseware hasn’t been typical, but it has given me the perfect balance of expertise to understand our customers, who are auditors and accountants looking to use technology to improve their daily workflows. At the beginning of my career, I followed my mother’s advice to take an accounting class in college. She insisted that understanding financial matters was crucial, no matter what career path I chose.

Once I entered the accounting world, I followed a fairly traditional career path. I also went on to earn a Master of Science in Accountancy from the University of Virginia. However, I found that while I can understand and work within traditional accounting frameworks, I also bring a different, non-linear approach to problem-solving, which ultimately led me to the world of software, analytics, and AI within the accounting industry.

My ability to bridge the gap between traditional accounting and innovative technologies has definitely positioned me well for my current leadership role at Caseware, and I am enjoying leveraging both my accounting expertise and my unconventional thinking to drive advancements in analytics and AI for our customers.

AI is transforming many industries, but why do you believe professional services, particularly audit and accounting, are uniquely positioned to benefit from AI advancements?

Our profession is highly regulated with an exceptionally high expectation for precision. This has historically made it difficult to adopt new technologies, as we can’t afford to ‘fail fast’ in auditing. The complex, judgment-intensive tasks we perform are not conducive to automation through previous technological innovations. As a result, the accounting profession has often been perceived as a technology laggard, not due to unwillingness, but because of the stringent requirements for reliability and accuracy in our work.

Generative AI represents a fundamental shift. Unlike previous technologies that focused primarily on automation, generative AI is designed to work alongside humans to enhance our capabilities rather than replace them. This aligns well with our existing processes, which already incorporate extensive human review and validation.

What are some common misconceptions about AI in the context of professional services, and how can these be addressed?

AI, like human professionals, isn’t perfect, and that’s why it’s essential to have a robust review process in place. The misconception that all AI is a ‘black box’ and therefore is categorically unusable is simply not true. Standards, including new International ethical guidelines, recognize the potential of AI and provide frameworks for responsible use. It’s not about avoiding AI entirely, but rather about ensuring proper oversight and validation to make the most of its capabilities to underpin the stability of markets in the best way we can.

To Know More, Read Full Interview @ https://ai-techpark.com/aitech-interview-with-danielle-supkis-cheek/

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Generative AI has swiftly become popular among marketers and has the potential to grow to a $1.3 trillion industry in the next 10 years. OpenAI’s ChatGPT is just one growth example—rocketing to over 100 million users in just two months of its release.

Many have hailed generative AI as a process-changing tool that can quickly produce swaths of content with minimal human intervention, drastically scaling content production. That’s the claim anyway. But as AI becomes more prevalent, its use in content production opens several questions — does generative AI actually produce quality content? Can it match what human marketers can produce?

With the digital landscape already saturated with content, marketers in the AI era need to fully understand the strengths and weaknesses of current generative tools so they can build (and protect) high-quality connections with their audiences.

Human-generated content beat out AI-generated content in every category.

Though the AI tools had strengths in some areas, no one tool mastered multiple criteria across our tests. When it comes to accuracy, readability, and brand style and tone, the AI tools could not reach the level of quality that professional content writers provided. It also lacked the authenticity of human-written content.

The lesson: Brands and marketers must keep humans at the center of content creation.

Unsurprisingly, AI is not the end-all-be-all solution for creating content that truly connects with human audiences.  

Yes, AI is an efficient and capable tool that marketers can leverage to supercharge specific content tasks. Using AI for tasks such as research, keyword analysis, brainstorming, and headline generation may save content creators money, time, and effort.

Even so, marketers should prioritize humanity in their writing. AI can only give us an aggregate of the staid writing available across the internet. But highly skilled human writers are masters of contextualization, tapping into the subtleties of word choice and tone to customize writing to specific audiences.

As some have pointed out, quantity can never win out over quality.

In the race to adopt AI tools, we must remember what makes content valuable and why it connects with human audiences. The online marketing landscape is becoming increasingly competitive, and brands can’t risk the ability to build trusting connections with consumers in their rush to streamline workflows. Ultimately, humans must remain the central focus as brands invest in unique and authentic content that connects.

To Know More, Read Full Article @ https://ai-techpark.com/ai-vs-human-content-quality/

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Joel, how have the unique challenges faced by small and medium-sized enterprises influenced their adoption of AI in identity management and security practices?

So we commission a biannual small to medium-sized enterprise (SME) IT Trends Report that looks specifically at the state of SME IT. This most recent version shows how quickly AI has impacted identity management and highlights that SMEs are kind of ambivalent as they look at AI. IT admins are excited and aggressively preparing for it—but they also have significant concerns about AI’s impact. For example, nearly 80% say that AI will be a net positive for their organization, 20% believe their organizations are moving too slowly concerning AI initiatives, and 62% already have AI policies in place, which is pretty remarkable considering all that IT teams at SMEs have to manage. But SMEs are also pretty wary about AI in other areas. Nearly six in ten (62%) agree that AI is outpacing their organization’s ability to protect against threats and nearly half (45%) agree they’re worried about AI’s impact on their job. I think this ambivalence reflects the challenges of SMEs evaluating and adopting AI initiatives – with smaller teams and smaller budgets, SMEs don’t have the budget, training, and staff their enterprise counterparts have. But I think it’s not unique to SMEs. Until AI matures a little bit, I think that AI can feel more like a distraction.

Considering your background in identity, what critical considerations should SMEs prioritize to protect identity in an era dominated by AI advancements?

I think caution is probably the key consideration. A couple of suggestions for getting started:

Data security and privacy should be the foundation of any initiative. Put in place robust data protection measures to safeguard against breaches like encryption, secure access controls, and regular security audits. Also, make sure you’re adhering to existing data protection regulations like GDPR and keep abreast of impending regulations in case new controls need to be implemented to avoid penalties and legal issues.

When integrating AI solutions, make sure they’re from reputable sources and are secure by design. Conduct thorough risk assessments and evaluate their data handling practices and security measures. And for firms working more actively with AI, research and use legal and technical measures to protect your innovations, like patents or trademarks.

With AI, it’s even more important to use advanced identity and authentication management (IAM) solutions so that only authorized individuals have access to sensitive data. Multi-factor authentication (MFA), biometric verification, and role-based access controls can significantly reduce that risk. Continuous monitoring systems can help identify and thwart AI-related risks in real time, and having an incident response plan in place can help mitigate any security breaches.

Lastly, but perhaps most importantly, make sure that the AI technologies are used ethically, respecting privacy rights and avoiding bias. Developing an ethical AI framework can guide your decision-making process. Train employees on the importance of data privacy, recognizing phishing attacks, and secure handling of information. And be prepared to regularly update (and communicate!) security practices given the evolving nature of AI threats.

To Know More, Read Full Interview @ https://ai-techpark.com/aitech-interview-with-joel-rennich/ 

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On an average, HR managers and recruiters go through a resume in almost six to seven seconds. It’s a really short time and shows that your resume must be outstanding and unique to catch their eye. Using difficult fonts, flashy designs, and a bad layout can become a reason for you to miss out an opportunity, even if you are well-qualified for that role.

Your resume tells about your past work history, skills, hobbies, competencies, etc. Just like many other industries, Artificial Intelligence (AI) can help you with writing your resume. Most people make silly mistakes or are unable to include all necessary information about themselves in their resume. An AI job search tool can help craft a flawless resume for you apart from just searching jobs.

How AI Tools Transform Resume Writing?

Instead of doing it by yourself, when you take the help of AI, it will ensure that your resume has the right format and headings.

Also, AI goes through the job posting and optimizes your resume based on it so that you have an edge over other candidates. This is how AI is transforming the art of writing resumes.

Suggest Ideal Templates

Most people choose a template for their resume and keep using it for all future applications. This is not the correct way because recruitment trends keep changing and not all organizations are looking for a similar thing.

A template may be good for a particular job opportunity but it doesn’t mean that it will work everywhere. AI tools suggest templates depending on the company you’re applying to. The right template will ensure clarity and visual appeal, highlighting relevant skills to impress HRs.

Analyzes Job Descriptions & Optimizes Your Resume Accordingly

You should never use the same resume for different job opportunities as every role demands different skills. AI tools carefully go through job descriptions and understand the requirements. They optimize your resume with several keywords and skills that recruiters are looking for.

Also, these tools will place relevant terms in such a way that recruiters surely see them while going through your resume. Using a single resume does not work anymore and you should use AI tools if you want a perfect resume based on the role you’re applying for.

Focuses on Your Top Skills & Achievements

Many people don’t put emphasis on their top skills and previous achievements when creating their resume. Recruiters won’t put in the effort to read every single word of your resume and it’s your duty to showcase your skills and experience in a way that they have high visibility.

When you use an AI job search tool, it will help you in highlighting the in-demand skills you have and your past work history relevant to the role. Even if you are well-qualified for a job, if your resume does not showcase your skills properly, you’ll miss out.

To Know More, Read Full Article @ https://ai-techpark.com/ai-elevates-resume-crafting/ 

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Another day, another AI headline. Meta has introduced new AI chatbots, embodied by celebrities, in a bid to mix information with entertainment. Amazon has invested up to $4B in its rival, Anthropic; and Google has launched Gemini, to compete with GPT-4. That’s just some of the AI stories within the last quarter involving three of the most influential companies in the technology sector.

Artificial Intelligence is booming. Its rapid development in 2023 has unlocked a wave of new possibilities and opportunities for the AI and machine learning ecosystem. But one of its beneficiaries isn’t. While AI stock has never been higher, we’ve not seen this optimism translate into the autonomous vehicle (AV) sector. This makes little sense. The development of AI and the future of autonomous vehicles is inextricably linked – the former quite literally powers the latter. So why is there this disparity in market confidence between the two sectors? And what does the surge in artificial intelligence mean for the AV sector as a whole?

The field of autonomous vehicles (AVs) has captured our imagination for decades. While self-driving cars are still a work in progress, the recent boom in artificial intelligence (AI) has the potential to be a game-changer. Let's explore how advancements in AI could transform the landscape of autonomous vehicles.

One of the most significant impacts of AI will be on the decision-making capabilities of AVs. AI algorithms, trained on vast amounts of driving data, can potentially react to complex situations faster and more consistently than human drivers.

The AV crystal ball

The challenges of AV at present are those of AI’s future. One of these big challenges revolves around data. An advanced driver assistance system (ADAS) or autonomous driving (AD) system relies on sensors (such as cameras and radar) to ‘see’ the world around them. The data these sensors collect is processed by machine learning to train an AI algorithm, which then makes decisions to control the car. However, handling, curating, annotating and refining the vast amounts of data needed to train and apply these algorithms is immensely difficult. As such, autonomous vehicles are currently pretty limited in their use cases.

AI developers outside the AV world are similarly drowning in data and how they collate and curate data sets for training is equally crucial. The issue of encoded bias resulting from skewed, low quality data is a big problem across sectors: bias against minorities has been found in hiring and loans, where in 2019 Apple’s credit card was investigated over claims its algorithm offered different credit limits for men and women. As applications of AI only continue to increase and reshape the world around us, it’s critical that the data feeding algorithms are correctly tagged and managed.

In other sectors, errors are more readily tolerated, even while bias harms. Consumers may not mind the odd mistake here and there when they enlist the help of ChatGPT, and even find these lapses amusing, but this leniency won’t last long. As reliance on new AI tools increases, and concern over its power grows, ensuring applications meet consumer expectations will be increasingly important. The pressure to close the gap between promise and performance is getting bigger as AI moves from science fiction to reality.

To Know More, Read Full Article @ https://ai-techpark.com/how-will-the-ai-boom-affect-autonomous-vehicles/ 

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