As a leader in the AI CRM Sales tech space I was curious how AI’s would evaluate competitive CRM/AI enhanced offerings and how likely it would be that it would be factual vs. the usual CRM marketing puffery we see on a daily basis. I was also curious how much AI “hallucination” would take place and whether or not it would be to the advantage of the AI parent company (in this case Microsoft) or just generalized AI hallucinations or perhaps non at all.
Copilot comparison of AI capabilities and features across Microsoft Dynamics, Salesforce CRM, Hubspot CRM:
This table provides a high-level overview of how each CRM utilizes AI to enhance the sales process. Microsoft Dynamics and Salesforce CRM offer more advanced AI capabilities, which are suitable for larger organizations or those with complex sales processes.
The challenge with this table is not knowing what is the “latest” and most correct information vs. what Copilot was able to access (and the time period). If I look at the cost, I think the research is a bit *old however, I look to my readers to help out and tell me what they think. How accurate is this table and what is AI marketing puffery vs. what these three CRM platforms can actually deliver.
HubSpot – I went to their website looking for a HubSpot pricing page (like Microsoft and Salesforce) and was intercepted by the worst AI chatbot I have seen this year. It refused to answer my questions, no matter my change in prompt, instead it was just sell, give me your email address, sell, sign up for demo, sell and my last contact with it was “Thanks Hubspot Chatbot – your performance has been so horrid that I have just taken your CRM off my consideration list.”
As my dear readers know AI must be constantly monitored by humanoids. In this case my guess is they turned up the aggressive sell chatbot feature and forgot the sentiment / human part of the CX equation. Will check back in a week to see if it was an AI hallucination or programmed in.
This is your average Blended AI SME Homosapien signing off and respectfully requesting your comments and perspective. Who is going to win or will it be a dark house like Sentia AI – that will take over the CRM landscape. Stay tuned!
The corporate landscape is changing faster than ever before and its speed is increasing exponentially.
The road to business and sales success which were easy to follow in yesteryear has been replaced with crooked pavement and too many potential twists and turns to easily predict the right path forward.
Artificial Intelligence (AI) is the reason for this corporate revolution, offering unprecedented opportunities for speed, growth, knowledge, and efficiency. However, as every comic book reader knows with great power comes great responsibility, and AI is no exception.
In fact, the biggest concern is that AI is moving so fast that what is legal or not, is in question as new precedents are set and new laws in Europe and the USA start to form. Sam Altman CEO of Open AI has even gone on record to state that the AI Revolution maybe moving too fast for Society to Adapt. Same with Business!
The challenge for any C-Suite team is understanding which AI risks are real vs. AI fear mongering.
Corporations must be vigilant when integrating new AI applications into their operations. They must be clear regarding the known risks and be prepared if their AI goes rogue how they are going to handle it. With AI you can’t know everything that is coming, but corporations must look at the big picture when implementing AI, and know the potentially amazing, good while being prepared for the ramifications of a bad AI install or employees using AI illegally (likely without even knowing it).
Top 10 AI Risks Corporations Face Today
AI Risk
Potential Impact
Risk Mitigation Strategies
Data Privacy
Unauthorized access to sensitive information – AI “sees everything”
Implement robust encryption and access controls
Bias in Decision-Making
Unfair treatment and discrimination
Regularly audit algorithms for bias and fairness
Security Vulnerabilities
Cyber-attacks exploiting AI weaknesses
Conduct frequent security assessments and updates
Compliance Risks
Fines and penalties for non-compliance
Stay updated with regulations and ensure AI adherence
Lack of Explainability
Difficulty in understanding AI decisions
Develop explainable AI models and provide transparency
Dependence on AI
Over-reliance leading to skill degradation
Encourage human oversight and continuous learning
Job Displacement
Loss of jobs due to automation
Invest in workforce reskilling and upskilling programs
Ethical Concerns
AI actions conflicting with moral values
Establish an AI ethics board and clear guidelines
Misinformation
Spread of false information by AI
Design AI with fact-checking and source verification
Intellectual Property Risks
Theft or misuse of AI-generated content
Secure intellectual property rights for AI creations
This article covers just ten current AI concerns and each of these is an entire paper with a risk mitigation strategy associated with it and a team of AI lawyers ready to deploy! If you’re interested in learning more check out Sentia AI’s interview with AI Lawyer Gary Kibel.
The long and the short of it is the rapidly evolving landscape of AI, corporations must stay ahead of these risks to harness AI’s full potential while maintaining trust and integrity. By proactively addressing these concerns, businesses can pave the way for a future where AI and human ingenuity work hand in hand for the betterment of society.
By Sentia AI’s Word Sorcerer & AI Jargon Decipherer
What’s the Buzz About Private LLMs?
Ah, my fellow digital wanderers! Gather ’round the virtual campfire, for today we delve into the clandestine realm of Private Large Language Models (LLMs). Picture this: a secret society of linguistic marketing and sales wizards, huddled in dimly lit chatrooms, whispering magic AI incantations to protect our words from prying algorithms. Yes, my friends, it’s time to demystify the enigma that is the Private LLM, lets see if the mystical golden dragon can protect your Castles AI Database.
Chapter 1: The Quest for Privacy
In the age of oversharing and data breaches, privacy is our golden fleece. Publicly available LLMs like GPT-3 are like chatty parrots—repeating everything they hear. But fear not! The Private LLM is a trusty invisibility cloak (TM Doctor Strange). It’s like whispering secrets to a mime—only you know what’s being said.
Chapter 2: Crafting Your Own LLM
Set Your Objectives: Before embarking on this epic journey, ask yourself: What’s your LLM’s purpose? Internal memos? Content creation? Or perhaps decoding ancient hieroglyphs? Define your quest, young linguist!
Choose Your Architecture: Imagine LLMs as magical Unicorn like creatures. You can fine-tune existing beasts, birth a new one from scratch, or adopt a friendly neighborhood open-source model (like GPT-2). Choose wisely, for your LLM shall inherit its lineage.
Data Collection and Preprocessing: Ah, the potion-making phase! Gather texts, poems, and cat memes (for err… balance). Cleanse them of typos, heresies, and misplaced semicolons. Tokenize like a caffeinated squirrel.
Training Your Model: Picture a wizard’s tower, filled with humming GPUs and mystical incantations. Training your LLM takes time—days, weeks, or until your beard grows longer than Gandalf’s. Did you say prompts create the best answers?
Securing the Model: Guard your LLM like Smaug guards his gold. Encrypt it, set traps, and hire a digital Cerberus. Remember, loose LLMs sink ships. AI risk is everywhere – every company wants to steal your data and learn your secrets! Your brave Private LLM – stands tall like a giant risk wall!
Chapter 3: The Legal Scroll
Why is this arcane knowledge legally crucial?
Well, my friends, imagine a world where LLMs spill secrets like gossiping witches. Legal contracts, confidential emails, and classified cat videos—all exposed! Private LLMs keep our secrets safe, like a dragon guarding its hoard. Lawyers nod approvingly. Yes, “this is the way” echo the Mandalorians.
Chapter 4: Marketing and Sales Sorcery
Behold, the five ways marketers and sales wizards wield Private LLMs:
Hyper-Personalized Emails: Picture an email that knows your soul better than your therapist. Private LLMs craft personalized pitches, making you feel like the protagonist of your own epic saga. With your magic AI marketing quill, you leap castle moats like King Arthur & Merlin– no mortal can ignore you anymore!
Content Generation Spells: Blogs, social media posts, and product descriptions—Private LLMs churn them out faster than a caffeinated scribe. Quality? As high as a dragon’s eyrie.
Sentiment Analysis Potions: LLMs sip from the cauldron of sentiment. They gauge customer feelings, predicting whether they’ll dance a jig or summon a storm. Like Sun Tzu said if you know your target, you know how to win.
Chatbot Enchantments: Ever chatted with a bot that understands your existential crisis? Thank the Private LLM. It’s like having a digital therapist who doesn’t judge your sock choices. Nor take a nap during your session.
Market Research Wizardry: LLMs analyze trends, decipher cryptic hashtags, and predict the next unicorn startup. They’re the Merlin to your Arthur.
And there you have it, dear reader! The Private LLM—a magical quill in our digital spell book. So go forth, build your LLM fortress, and remember: “With great language comes great responsibility.”
SEO Tags: #LLMs #LLM #PrivateLLM #AI #ChatGPT #OpenAI #marketing #digitalmarketing
It’s no secret that AI is transforming industries, and manufacturing is no exception. But what about the heart of the beast – sales? Is AI poised to disrupt the delicate dance between manufacturers and their customers? Buckle up, folks, because the answer is a resounding yes – and it’s a change with game-changing potential.
Let’s blast through the hype and explore how AI is set to impact manufacturing sales tech in three key ways:
1. Supercharged Sales Intelligence: Imagine having a precog on your sales team. AI-powered insights are here to do just that. By analyzing vast datasets, AI can predict customer needs, buying patterns, and even churn risk with uncanny accuracy. Think personalized product recommendations, proactive outreach to at-risk accounts, and targeted campaigns that hit bullseyes, not broadsides. No more cold calls, folks – we’re talking laser-focused engagement that builds genuine relationships.
2. The Rise of the Sales Cyborg: Remember Robocop? Okay, maybe not that extreme (yet). But envision a future where sales reps wield AI-powered tools that streamline their every move. Chatbots handle routine inquiries, freeing up reps for high-value conversations. Virtual assistants schedule meetings, draft proposals, and even analyze customer sentiment during calls. It’s not about replacing reps – it’s about amplifying their superpowers, giving them the bandwidth to focus on what they do best: building trust and closing deals.
3. The Customer Experience Goes Hyperdrive: We all know happy customers are repeat customers and the best sales referrals. AI properly applied at the right time in each companies unique sales process can take the manufacturing customer experience to a whole new level. Marketing and sales work together transparently. Each can easily see how to impact the customer experience – who is using what content, for what purpose, what phase of the sales cycle and how is it impacting (good or bad) that part of the sales cycle? All the data can be seen and shared in ways only an AI generated dream was capable of just two short years ago!
Imagine:
Real-time product customization: A customer tweaks a machine’s specs online, and AI instantly calculates pricing and delivery timelines. Boom – gone are the days of slow, cumbersome quote processes.
Predictive maintenance: Forget reactive repairs. AI monitors equipment performance, predicting potential issues before they disrupt production. Customers can proactively schedule maintenance, minimizing downtime and maximizing efficiency.
Virtual showrooms with augmented reality: Can’t afford to bring a behemoth machine to every client? No problem! AR lets customers virtually interact with products, even in their own facilities. The result? Faster decision-making and boosted confidence.
Challenges and the Road Ahead: Of course, with great power comes great responsibility. Implementing AI effectively requires careful planning and consideration. Data security, bias mitigation, and ethical considerations are paramount. Additionally, retraining and upskilling sales teams will be crucial. Remember, AI is a tool, not a replacement. The human touch of relationship building and expert advice will always be irreplaceable.
So, is AI the death knell of the traditional manufacturing salesperson? Absolutely not. It’s the dawn of a new era, where technology empowers reps to reach their full potential. Those who embrace AI and adapt their skillsets will not only survive – they’ll thrive, leaving outdated sales tactics in the dust. This isn’t a revolution to fear, it’s an invitation to evolve. So, embrace the AI revolution, manufacturers, and get ready to take your sales game to warp speed. The future of manufacturing is looking brighter than ever.
Let’s discuss! How do you see AI impacting manufacturing sales? Share your thoughts in the comments below.
There are so many ways you can use AI in sales these days, it’s hard to know where to start, especially if you’re a newbie to all of the excitement. So, this article will focus on something almost everyone in the business world uses, knows, and understands how It can be used right now, on every business persons favorite, LinkedIn.
Using AI with LinkedIn selling can enhance your sales and marketing efforts by automating tasks, providing valuable insights, and streamlining processes. As noted in previous articles, to maximize AI’s usefulness it requires a combination of Blended AI* and Augmented AI** to maximize its impact.
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10 ways to use Augmented & Blended AI with LinkedIn
1. Personalized messaging: AI-powered tools can analyze data from LinkedIn profiles and interactions to create personalized messages that resonate with individual prospects, increasing engagement and response rates.
2. Relationship insights: AI can analyze communication patterns and interactions with prospects to provide valuable relationship insights, such as the best times to reach out or the most effective ways to engage with specific individuals.
3. Lead generation and prospecting: AI algorithms can help identify and prioritize potential leads based on specific criteria identified in your sales process, such as job titles, industries, or geographic locations, making your prospecting efforts more efficient.
4. Sales forecasting: AI-driven analytics can analyze historical data, sales patterns, and market trends to provide more accurate sales forecasts, helping you plan and strategize your selling efforts better.
5. Competitor analysis: AI can gather data on competitors’ activities and strategies on LinkedIn, providing valuable insights to refine your own selling approach and stand out in the market.
6. Performance tracking and analytics: AI-driven analytics can measure the effectiveness of your LinkedIn selling efforts, tracking key performance indicators (KPIs) like response rates, conversion rates, and engagement metrics. This data allows you to continuously improve your strategies.
7. Content recommendations: AI can analyze user behavior and preferences to suggest relevant content, such as articles, blog posts, or videos, that align with your prospects’ interests and pain points.
8. Social listening and sentiment analysis: AI tools can monitor conversations and discussions on LinkedIn to gauge the sentiment around your brand and industry. This information can help you tailor your messaging and identify potential opportunities or challenges.
9. Automated follow-ups: AI-powered sales automation tools can handle routine follow-up tasks, sending timely messages and reminders to prospects, helping to maintain engagement and nurture leads.
10.Chatbots for instant responses: Implement AI-driven chatbots on your LinkedIn profile to provide instant responses to common questions, qualify leads, and engage with prospects at any time, improving customer experience and response times.
There is no single AI tool (yet) that can accomplish all ten use cases noted on my list and it isn’t necessarily in order of usefulness. Instead, each seller must ascertain what is most important in their sales efforts and then use Blended AI to attack their sales patch in a coordinated and concise manner. Best practices are to pick a vendor that know what is actually working to advise when to use it and when not to, because:
The key isn’t using AI.
The key is using the right AI with your already successful, winning Sales Process and applying the right form of AI at the right stage in the sales process. That is the Winning Ticket!!!
Bottom line
By leveraging Augmented and Blended AI in your LinkedIn selling efforts, you can streamline working sales processes, deliver a significantly more personalized experience for your target audience, and make data-driven decisions (not just gut feelings), ultimately increasing each seller’s success rate by connecting with the best prospects and converting them into valuable customers.
*Blended Artificial Intelligence Is the amalgamation of different artificial intelligence techniques or approaches to achieve more robust and effective solutions. It involves integrating multiple AI models, algorithms, and / or technologies to leverage their respective strengths and compensate for their weaknesses. See Wikipedia:
** Augmented artificial intelligence is a design pattern for a human-centered partnership model of people and artificial intelligence (AI) working together to enhance cognitive performance, including learning, decision making and new experiences.
Venture Capitalists weren’t born in the Matrix but sometimes it can feel that way if you’re a startup looking for capital.
They will invest in startups that have the right idea and key people to solve a big hairy problem with a large amount of potential revenue or users, needed for a successful VC exit. Whether its in the Metaverse or Matrix all VC’s want one thing.
Startups must scale very quickly to be successful.
Developing a scalable sales tech stack takes time and requires a very flexible and rapidly scalable CRM platform to manage all the sales tech data pipes. Startups must focus on keeping things as simple as possible for end users but still give them the right actions to do at the right time. This can be expensive for startups since they are often forced to pivot as they learn what is working or not. By building flexible and scalable tech systems from the beginning their odds of succeeding improve dramatically.
Entrepreneurs must consider what a VC or Investor maybe looking at when evaluating their company for a potential investment – at least from “What are they Going to Sell” perspective.
With that in mind. This is what VCs are looking for when evaluating your startup sales tech stack:
5 Reasons Why VCs Want You to use CRM / Sales Technology
Improved Revenue: A high-quality CRM properly implemented can help a Startup manage its sales pipeline more efficiently, resulting in improved sales and revenue. This helps boost the startup’s valuation and obviously more attractive to investors.
Superior Customer Engagement: A CRM can help a startup improve its customer experience by providing insights into customers behavior, preference and needs. This can help the startup develop better products and services, resulting in increased customer loyalty and higher revenue.
Operational Efficiency: A high-quality CRM can help a startup streamline its sales and marketing processes, resulting in improved operational efficiency. This can lead to cost saving and increases profitability, which can make the startup more attractive to investors.
Data Insights: A CRM can provide valuable data insights that can help a startup make more informed business decisions. This can help the startup develop more effective strategies, leading to improved revenue and profitability.
Scalability: A top CRM can help a startup scale its sales and marketing efforts more effectively and quickly. This can help the startup expand its customer base and grow its revenue, which can make it more attractive to investors.
Investors want startups to succeed or fail fast!
Their investment window is dependent on some of their investments growing quickly and that is where they need to focus, while others will fail and need to get off the books/harvest patents.
Many VCs prefer that you use Salesforce as it is the number one selling CRM.
They know they can get people to configure and implement the system, most sales people are familiar with it and it’s enterprise grade so scaling isn’t a big concern. It ticks a big funding box.
Next – whether a VC prefers a startup with Salesforce CRM or no CRM would depend on several factors. In general, if a startup already has a Salesforce CRM, it often indicates that they already have a well defined sales process and are using data to inform their decision-making. This makes their evaluation easier as they can see actual numbers vs. a hockey stick graph.
However, the absence of a CRM doesn’t always mean a startup is less attractive. VC’s maybe willing to invest in early stages of development – especially if a clear value proposition is backed by a clear sales process tracked to achieve rapid growth. Often VC’s have favorite CRM implementation partners that can quickly come in and set things up because they have a repeatable process in place.
One other way VC’s use CRM’s is to look at the numbers every day. Leading CRM AI packages (Such as Sentia) show VC’s every one of their investments in a simple dashboard showing daily sales, outbound activities and tracking to quota. They don’t have to call the CEO, they see it in real time. Most VCs like this because it reduces surprises and uncertainty.
Ultimately, whether a startup has a Salesforce CRM or no CRM it’s only one factor that VCs consider when evaluating potential investment opportunities. The most important factors are the startups overall business plan, the problem they plan to solve, quality of chosen team, potential for growth and profitability, and often most importantly how does your startup fit in the VC investment strategy and ten-year plan.
2023 will go down as the year of AI in business school history books. Rarely has a new technology evolved so quickly, gained wide spread use nor stirred as much concern as Artificial Intelligence. Regardless of where people stand on the use of AI (see 1984 “The Terminator“) it is already well entrenched in the business world and its use is only going to expand.
In this regard I’m going to focus on the top ten applications of AI in Sales systems so far. Sales tech stacks are usually the first ones impacted in any business organization because it is the most visible profit (or loss center). There is zero doubt that AI is rapidly transforming the sales landscape. We’re seeing the introduction of so many innovative applications that enhance efficiency, improve customer experiences, and boost sales performance its hard to know where to start, nor completely understand what is coming.
With that being said I’m going to put a stake in the proverbial ground and start with what I think are the top 10 things I see AI doing right now that are dramatically affecting sales systems:
2023’s Top 10 new applications of AI in sales tech:
AI-powered Sales Coaching and Training: Coaching tools can analyze every sales conversation or interaction, identify areas for improvement, and provide real-time feedback for sales reps. This AI augmented and personalized approach helps reps refine their communication skills, build stronger relationships with potential customers, and close more deals. It does this without a manager, trainer or supervisor needing to spend “time” with a sales rep. It can be self sourced and used when the rep wants it or by a manager to see how a rep is performing without having to have those “difficult conversations” where a customer calls and says XYZ is terrible, you need to get rid of them! It is no longer a she said, he said as it is all recorded.
AI-driven Predictive Sales Forecasting: AI algorithms analyze historical sales data, market trends, and customer behavior to predict future sales performance with greater accuracy (this assumes clean data!). This enables sales teams to make informed decisions about resource allocation, target customer segments, and sales strategies. As always the better the data that is input (Sales Reps are notorious for not using their CRMs) the more likely AI can improve predictive forecasting.
AI-enabled Lead Qualification and Prioritization: AI models assess leads based on various factors, such as firmographic data, website behavior, and engagement patterns, to identify the most promising leads. This helps sales reps focus their efforts on the most qualified leads, increasing their chances of closing deals.
AI-powered Sales Content Generation and Personalization: AI tools can generate personalized sales and marketing content, such as email templates, social media posts, and sales pitches, tailored to the specific needs and interests of each buyer persona/prospect. This personalized approach can increase engagement and conversion rates.
AI-driven Conversational Sales Chatbots: AI chatbots can engage in real-time conversations with potential customers, answering questions, providing product information, and scheduling demos. This 24/7 availability and personalized interaction can enhance customer experience and capture leads early in the sales cycle.
AI-powered Sales Incentive Compensation and Optimization: AI algorithms can analyze sales data and performance metrics to determine optimal incentive compensation plans that motivate reps and drive sales growth.
AI-enabled Sales Territory Planning and Optimization: AI models can analyze market data, customer demographics, and sales performance to identify optimal sales territories that maximize revenue potential.
AI-powered Sales Prospecting and Discovery: AI tools can identify and prioritize potential customers based on various factors, such as firmographic data, website behavior, and social media engagement, helping sales reps uncover new opportunities.
AI-driven Sales Opportunity Management and Deal Coaching: AI can analyze sales opportunities, identify buyer intent, potential risks and roadblocks, and provide real-time coaching to sales reps to increase their chances of closing deals.
AI-powered Sales Workflow Automation: AI tools can automate repetitive sales tasks, such as data entry, email follow-ups, and scheduling appointments, freeing up reps to focus on more strategic activities.
The key element to all ten of these AI use case applications is “CAN.” Every single one of these requires a blended AI experience to make it work. None of these can successfully operate without human interaction either in the development, use or tweaking of them. In fact AI is so new in most of these applications that if you don’t have a trained human available to constantly watch, improve and tweak any of these AI’s on a regular basis I would be very concerned about deploying them.
With that in mind we need to focus on the number one tool that most sales reps both hate and must use on a fairly regular basis, CRM (Salesforce says 26% daily usage for CRMs). CRMs or Customer Relationship Management software is an $80Billion dollar business but the failure rates are surprisingly high. I wondered if AI could solve this problem and turned to CRM experts for the answer.
I spoke with renowned CRM expert and best selling Author Mike Hudlow (see “How not to F*CK up a CRM system“) on these top ten AI solutions and asked him – What is the biggest problem with CRM systems right now?
Mike said: “”Human Change Management” is the key reason systems fail. But, unfortunately there are many reasons that this can occur. The reality is that people like to blame the technical system itself but any modern CRM system is capable of improving a companies CRM process/workflow. The challenge for any program/product/project manager, CIO, CTO, CMO or person in charge of the CRM to make it both welcomed and desired. Sounds scary human doesn’t it? A CRM can and will be resisted by: 1) those that don’t trust it, think its needed and/or believe that others will steal their own personal IP, 2) those divisions within a company that think it is too expensive, 3) People or teams that believe that the system will replace another system to which they are attached (career or emotionally ), 3) or people that actually or perceptually believe it creates more work, and 4) leaders that feel it infringes upon their own autonomy.”
My second question to Michael was can any of these top ten AI enhancements solve those problems?
Mike replied: “At the end of the day an AI supplemental tool can improve many of these as it makes the native CRM tool “bend” to their own style and will make them more comfortable with the AI’s ability to bridge the gap, bend to their own style, and allow them to let the CRM system they don’t feel comfortable with be more “human” and meet their own specific needs”
I then turned to AI Visionary and Sales Process Expert David Forder for an AI perspective on CRMs and AI. My question was simple yet nuanced. Can AI solve the biggest problems in CRM i.e., no sales rep wants to use it?
David replied: “The biggest issue that CRMs face is a lack of user adoption. 74% of customer facing staff refuse to use their CRM every single day. Yet companies spend billions of dollars on it! Adding AI into the mix has the potential to make this even worse! Unless any AI integration improves the underlying complexity of using a CRM and makes them simpler and more effective it will definitely make it worse not better! This has to be the focus of AI.”
I then asked Mr. Forder – how do you make it simpler? Get sellers using it?
David’s reply: “The key to making the CRM simpler is to ignore what will appeal to C-Suite i.e. ignore the focus on data heavy screens, reports and dashboards and re-engineer the CRM to meet the needs of the bulk of the users – those customer facing teams. Design the CRM to meet their daily needs, so they want to use it as it does the work for them. If you do this they will embrace their CRM and it can then work effectively for C-Suite as the data will actually be in the system! That’s our focus at Sentia AI! Have your CRM do most of the work for them, tell them what to do next and watch usage rates explode!”
Both Mike’s and David’s battle scars, extensive CRM implementations, sales experience and knowledge made me think I should interview both of them and get their thoughts on video for everyone to learn from. So we’re going to do it and here is the link:
This may turn into two video segments as the topic is so timely, important and I found that the breadth and depth of their CRM and AI system implementation experience was quite simply amazing!
These gentlemen have their finger on the pulse of sales, AI & CRM implementation success. It will be a great how to “fix it” roundtable.
Please join us on November 29th for an in-dept on how not to F*CK up A CRM system with AI!
David is an investor and executive director at Sentia AI – The Intelligence Engine, a next generation AI sales enablement technology company and Salesforce partner. Dave’s passion for helping people with their AI, sales, marketing, business strategy, startup growth and strategic planning has taken him across the globe and spans numerous industries. You can follow him on TwitterLinkedIn or on Sentia Says.
Unless you have been like the proverbial Ostrich with its head under the sand AI is here and making its presence felt quickly! Within a couple of years it will no longer be which company is using AI, rather it will be which company isn’t?
Since sales has the most scrutiny and oversight within the majority of companies (see CRO’s Get Fired First) it is often the first place AI is applied, for many good reasons. Sales rep turnover is usually high, there is lots of training (see Blended AI for Sales Rep Training) that needs to take place and companies spend a small fortune on hiring, training and getting reps “field ready). Also reps want new tech that works (if it doesn’t they will refuse to use it) and are used to being the first to use it.
AI is that “new” tech and many companies have already put AI implementation strategies into place (See CEO’s Must have an AI Strategy Plan) and those that don’t will, or they can fall behind competitors. The biggest challenge is AI is so new that top quality talent is hard to source, evaluate and hold onto. Many organizations (especially those using the number one CRM Salesforce) want to use AI strategy consultants that are also Salesforce partners. They know that these certified partners are the key to plan, strategize, and successfully implement AI.
The biggest challenge is finding the right one. There aren’t many case studies or client testimonials out there (yet) since it is so new. Falling back on past partner evaluation techniques are a starting point. However, the most advanced AI Salesforce partners are often smaller and harder to find (See Sentia AI).
With that in mind here are 7 high level tips for Selecting the right Salesforce partner with AI capabilities. Organizations looking to leverage artificial intelligence within their Salesforce ecosystem often have to look far and wide to find them. The following tips will act as a guide to help you in making an informed decision:
Check AI Certifications and Expertise: Ensure that the Salesforce partner possesses relevant certifications and a track record in AI. Look for certifications or experience with Salesforce Einstein Analytics and Discovery Consultant, which demonstrate expertise in leveraging AI within the Salesforce platform. If you’re not going to use Einstein / Discover – it isn’t as important.
Evaluate AI Use Cases and Experience: Assess the partner’s experience in developing as well as implementing AI solutions, especially within the Salesforce environment. Look for case studies or examples of successful AI integrations that align with your business needs. A partner with diverse AI use cases demonstrates versatility. Don’t pass on an AI Salesforce certified partner if they have limited or even no case studies – remember AI is in its infancy – be on the people at the company first and foremost, not slick marketing materials.
Assess Industry-Specific Knowledge: Industry expertise is crucial for understanding the unique challenges and opportunities within your sector. Choose a partner with a deep understanding of your industry, as this knowledge will be beneficial when tailoring AI solutions to your specific requirements.
Check Integration Capabilities: AI solutions often require seamless integration with existing systems. Ensure that the Salesforce partner has experience integrating AI capabilities with Salesforce and other relevant tools in your technology stack. This capability is crucial for a cohesive and efficient implementation.
Verify Data Security and Compliance: AI involves handling sensitive data, so it’s vital that your Salesforce partner prioritizes data security and complies with relevant regulations. Request information on their data protection measures and ensure they align with your organization’s compliance requirements.
Evaluate Training and Change Management Support: Assess the partner’s approach to training and change management. AI implementations often necessitate a shift in processes and workflows, so your partner should provide comprehensive training programs and support for change management to ensure successful adoption.
Consider Scalability and Future-Readiness: Select a partner with a focus on scalability and future-readiness. The AI solutions implemented should be scalable to accommodate your organization’s growth, and the partner should stay abreast of advancements in AI technology and Salesforce updates to ensure ongoing relevance.
Bonus Tips: Look for all in one help. Salesforce partners that can evaluate your business needs, sales process, configure Salesforce, then train your people are far more valuable than having to go out and find 3 separate partners to do each phase. It will cost a lot more in both time and money to do this and perhaps most importantly something is almost always lost with every handoff along the way. Also make sure the partner is going to be with you long term – AI is so new it is guaranteed to require tweaks, adjustments and outright replacement along the way. A partner with a history of run and gun is the last one you need right now. Check references to ensure they will work with you long after the sale is completed.
Seek Client References and Feedback: Request references from the Salesforce partner’s past clients who have implemented AI solutions. Gather feedback on their experiences, challenges faced, and the overall success of the projects. This firsthand information can be invaluable in your decision-making process.
By considering these tips, doing your homework and keeping an open mind to new partners that are ahead of the game, you can enhance your chances of selecting a Salesforce partner with the right AI capabilities. Finding that special, highly qualified partner to effectively integrate artificial intelligence into your Salesforce environment is the key to your future AI success!
In a surprising turn of events, OpenAI, the renowned organization dedicated to developing artificial intelligence responsibly, finds itself at the center of controversy. The founder’s recent departure, allegedly due to a lack of transparency in internal communications, has raised eyebrows and sparked discussions about the intersection of ethics and profit in the realm of artificial intelligence.
The Departure:
Over the weekend, OpenAI’s founder stepped down amid accusations of inconsistent candor in communications. The vague reasoning behind this decision has fueled speculation on social media, leaving both the tech community and the general public curious about what might be happening behind closed doors.
The Stakes:
The significance of this shakeup extends beyond the internal dynamics of OpenAI. Artificial intelligence, often considered a potential existential threat to humanity, demands trustworthiness and stability from those leading its development. OpenAI, originally positioned as a not-for-profit organization, faces scrutiny as questions arise about the compatibility of responsible AI development and profit-driven motives.
Altruism Meets Capitalism:
OpenAI’s mission to prioritize responsible tech development over profit is now in the spotlight. As the world’s media closely watches the aftermath of this leadership change, concerns about potential hidden agendas within the organization may come to light. If the conflict indeed revolves around prioritizing profit over ethical considerations, it raises broader questions about the feasibility of balancing responsible AI with profit-driven initiatives.
Microsoft’s Role:
With Microsoft owning a significant 49% stake in OpenAI, the tech giant is now under increased scrutiny. Not only did Microsoft absorb two ex-OpenAI entrepreneurs, but it also granted the ousted founder a position within its ranks. As the drama unfolds, Microsoft’s potential influence over OpenAI’s future is a topic of speculation. The private company, valued at around $90 billion, may face further upheaval as employees express discontent over recent changes.
The clash at OpenAI serves as a stark reminder of the challenges inherent in navigating the delicate balance between ethics and profitability in the development of artificial intelligence. As the tech community awaits further developments, the incident prompts broader reflections on the future of responsible AI and the role of profit-driven interests in shaping the trajectory of this transformative technology.
